diff --git a/.github/workflows/linting.yml b/.github/workflows/linting.yml
index a04cc30e005..d4460e25bff 100644
--- a/.github/workflows/linting.yml
+++ b/.github/workflows/linting.yml
@@ -48,7 +48,7 @@ jobs:
           pip install types-pytz types-requests types-termcolor types-tabulate types-PyYAML types-python-dateutil types-setuptools types-six
       - run: bandit -x ./tests -r . || true
       - run: black --diff --check .
-      - run: codespell --ignore-words-list=vai,mis,gard,commun,parana,statics,ro,zar,zlot,jewl,ba,buil,coo,ether,hist,hsi,mape,navagation,operatio,pres,ser,yeld,shold,ist,varian,datas,ake,creat,vie,hel,ket,toke,certi,buidl,ot,te,buda,shs,welp --quiet-level=2 --skip=./tests,.git,*.css,*.csv,*.html,*.ini,*.ipynb,*.js,*.json,*.lock,*.scss,*.txt,*.yaml,./build/pyinstaller,./website/config.toml -x openbb_terminal/economy/fedreserve_model.py
+      - run: codespell --ignore-words-list=vai,mis,gard,commun,parana,statics,ro,zar,zlot,jewl,ba,buil,coo,ether,hist,hsi,mape,navagation,operatio,pres,ser,yeld,shold,ist,varian,datas,ake,creat,vie,hel,ket,toke,certi,buidl,ot,te,buda,shs,welp,fo,nwe --quiet-level=2 --skip=./tests,.git,*.css,*.csv,*.html,*.ini,*.ipynb,*.js,*.json,*.lock,*.scss,*.txt,*.yaml,./build/pyinstaller,./website/config.toml -x openbb_terminal/economy/fedreserve_model.py
       - run: ruff .
       - run: mypy --ignore-missing-imports openbb_terminal
       - run: pylint terminal.py openbb_terminal tests
diff --git a/openbb_sdk/extensions/charting/openbb_charting/charting_router.py b/openbb_sdk/extensions/charting/openbb_charting/charting_router.py
index 8bf1b9440c9..f259b6b385b 100644
--- a/openbb_sdk/extensions/charting/openbb_charting/charting_router.py
+++ b/openbb_sdk/extensions/charting/openbb_charting/charting_router.py
@@ -238,6 +238,722 @@ def news_sectornews(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
     )
 
 
+def providers_benzinga_global_news_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/benzinga/global/news/standardized` does not have a charting function"
+    )
+
+
+def providers_benzinga_stock_news_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/benzinga/stock/news/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_key_executives_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/key/executives/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_global_news_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/global/news/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_news_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/news/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_income_statement_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/income/statement/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_balance_sheet_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/balance/sheet/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_cash_flow_statement_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/cash/flow/statement/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_share_statistics_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/share/statistics/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_major_indices_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/major/indices/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_revenue_geographic_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/revenue/geographic/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_revenue_business_line_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/revenue/business/line/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_institutional_ownership_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/institutional/ownership/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_company_overview_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/company/overview/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_insider_trading_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/insider/trading/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_ownership_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/ownership/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_e_s_g_score_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/e/s/g/score/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_e_s_g_sector_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/e/s/g/sector/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_e_s_g_risk_rating_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/e/s/g/risk/rating/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_price_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/price/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_price_target_consensus_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/price/target/consensus/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_price_target_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/price/target/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_analyst_estimates_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/analyst/estimates/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_earnings_calendar_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/earnings/calendar/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_earnings_call_transcript_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/earnings/call/transcript/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_historical_stock_splits_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/historical/stock/splits/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_historical_dividends_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/historical/dividends/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_key_metrics_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/key/metrics/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_s_e_c_filings_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/s/e/c/filings/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_treasury_rates_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/treasury/rates/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_executive_compensation_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/executive/compensation/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_crypto_price_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/crypto/price/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_crypto_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/crypto/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_major_indices_price_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/major/indices/price/standardized` does not have a charting function"
+    )
+
+
+def providers_fmp_forex_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/forex/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_stock_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/stock/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_stock_news_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/stock/news/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_balance_sheet_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/balance/sheet/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_income_statement_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/income/statement/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_cash_flow_statement_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/cash/flow/statement/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_stock_price_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/stock/price/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_crypto_price_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/crypto/price/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_crypto_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/crypto/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_major_indices_historical_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/major/indices/historical/standardized` does not have a charting function"
+    )
+
+
+def providers_polygon_major_indices_price_standardized(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/major/indices/price/standardized` does not have a charting function"
+    )
+
+
+def providers_benzinga_global_news_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/benzinga/global/news/simple` does not have a charting function"
+    )
+
+
+def providers_benzinga_stock_news_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/benzinga/stock/news/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_key_executives_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/key/executives/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/historical/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_global_news_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/global/news/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_news_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/news/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_income_statement_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/income/statement/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_balance_sheet_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/balance/sheet/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_cash_flow_statement_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/cash/flow/statement/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_share_statistics_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/share/statistics/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_major_indices_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/major/indices/historical/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_revenue_geographic_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/revenue/geographic/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_revenue_business_line_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/revenue/business/line/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_institutional_ownership_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/institutional/ownership/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_company_overview_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/company/overview/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_insider_trading_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/insider/trading/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_ownership_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/ownership/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_e_s_g_score_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/e/s/g/score/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_e_s_g_sector_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/e/s/g/sector/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_e_s_g_risk_rating_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/e/s/g/risk/rating/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_stock_price_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/stock/price/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_price_target_consensus_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/price/target/consensus/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_price_target_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/price/target/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_analyst_estimates_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/analyst/estimates/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_earnings_calendar_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/earnings/calendar/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_earnings_call_transcript_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/earnings/call/transcript/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_historical_stock_splits_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/historical/stock/splits/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_historical_dividends_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/historical/dividends/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_key_metrics_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/key/metrics/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_s_e_c_filings_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/s/e/c/filings/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_treasury_rates_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/treasury/rates/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_executive_compensation_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/executive/compensation/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_crypto_price_simple(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/crypto/price/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_crypto_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/crypto/historical/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_major_indices_price_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/major/indices/price/simple` does not have a charting function"
+    )
+
+
+def providers_fmp_forex_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/fmp/forex/historical/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_stock_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/stock/historical/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_stock_news_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/stock/news/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_balance_sheet_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/balance/sheet/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_income_statement_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/income/statement/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_cash_flow_statement_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/cash/flow/statement/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_stock_price_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/stock/price/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_crypto_price_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/crypto/price/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_crypto_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/crypto/historical/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_major_indices_historical_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/major/indices/historical/simple` does not have a charting function"
+    )
+
+
+def providers_polygon_major_indices_price_simple(
+    **kwargs,
+) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+    raise NotImplementedError(
+        "Command `providers/polygon/major/indices/price/simple` does not have a charting function"
+    )
+
+
 def qa_normality(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
     raise NotImplementedError(
         "Command `qa/normality` does not have a charting function"
@@ -1026,9 +1742,9 @@ def stocks_options_dte(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
     )
 
 
-def stocks_options_eodchain(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+def stocks_options_historicalchain(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
     raise NotImplementedError(
-        "Command `stocks/options/eodchain` does not have a charting function"
+        "Command `stocks/options/historicalchain` does not have a charting function"
     )
 
 
diff --git a/openbb_sdk/extensions/crypto/openbb_crypto/crypto_router.py b/openbb_sdk/extensions/crypto/openbb_crypto/crypto_router.py
index 21a0024cff5..ac89f01cc92 100644
--- a/openbb_sdk/extensions/crypto/openbb_crypto/crypto_router.py
+++ b/openbb_sdk/extensions/crypto/openbb_crypto/crypto_router.py
@@ -13,12 +13,12 @@ router = Router(prefix="")
 
 
 # pylint: disable=unused-argument
-@router.command(model="CryptoEOD")
+@router.command(model="CryptoHistorical")
 def load(
     cc: CommandContext,
     provider_choices: ProviderChoices,
     standard_params: StandardParams,
     extra_params: ExtraParams,
 ) -> OBBject[BaseModel]:
-    """Crypto EOD Price."""
+    """Crypto Historical Price."""
     return OBBject(results=Query(**locals()).execute())
diff --git a/openbb_sdk/extensions/economy/openbb_economy/economy_router.py b/openbb_sdk/extensions/economy/openbb_economy/economy_router.py
index ed2fd60ffa9..ae483167b06 100644
--- a/openbb_sdk/extensions/economy/openbb_economy/economy_router.py
+++ b/openbb_sdk/extensions/economy/openbb_economy/economy_router.py
@@ -40,14 +40,36 @@ def cpi(
     return OBBject(results=Query(**locals()).execute())
 
 
-@router.command(model="MajorIndicesEOD")
+@router.command(model="MajorIndicesHistorical")
 def index(
     cc: CommandContext,
     provider_choices: ProviderChoices,
     standard_params: StandardParams,
     extra_params: ExtraParams,
 ) -> OBBject[BaseModel]:
-    """Get OHLCV data for an index."""
+    """Get historical  levels for an index."""
+    return OBBject(results=Query(**locals()).execute())
+
+
+@router.command(model="EuropeanIndexHistorical")
+def european_index(
+    cc: CommandContext,
+    provider_choices: ProviderChoices,
+    standard_params: StandardParams,
+    extra_params: ExtraParams,
+) -> OBBject[BaseModel]:
+    """Get historical close values for select European indices."""
+    return OBBject(results=Query(**locals()).execute())
+
+
+@router.command(model="EuropeanIndexConstituents")
+def european_index_constituents(
+    cc: CommandContext,
+    provider_choices: ProviderChoices,
+    standard_params: StandardParams,
+    extra_params: ExtraParams,
+) -> OBBject[BaseModel]:
+    """Get  current levels for constituents of select European indices."""
     return OBBject(results=Query(**locals()).execute())
 
 
@@ -58,7 +80,7 @@ def available_indices(
     standard_params: StandardParams,
     extra_params: ExtraParams,
 ) -> OBBject[BaseModel]:
-    """AVAILABLE_INDICES."""
+    """Lists of available indices from a provider."""
     return OBBject(results=Query(**locals()).execute())
 
 
diff --git a/openbb_sdk/extensions/forex/openbb_forex/forex_router.py b/openbb_sdk/extensions/forex/openbb_forex/forex_router.py
index d82014036ce..28396d45e55 100644
--- a/openbb_sdk/extensions/forex/openbb_forex/forex_router.py
+++ b/openbb_sdk/extensions/forex/openbb_forex/forex_router.py
@@ -25,7 +25,7 @@ def pairs(
 
 
 # pylint: disable=unused-argument
-@router.command(model="ForexEOD")
+@router.command(model="ForexHistorical")
 def load(
     cc: CommandContext,
     provider_choices: ProviderChoices,
diff --git a/openbb_sdk/extensions/futures/openbb_futures/futures_router.py b/openbb_sdk/extensions/futures/openbb_futures/futures_router.py
index cced115f570..ca1da1fd2ea 100644
--- a/openbb_sdk/extensions/futures/openbb_futures/futures_router.py
+++ b/openbb_sdk/extensions/futures/openbb_futures/futures_router.py
@@ -13,14 +13,14 @@ router = Router(prefix="")
 
 
 # pylint: disable=unused-argument
-@router.command(model="FuturesEOD")
+@router.command(model="FuturesHistorical")
 def load(
     cc: CommandContext,
     provider_choices: ProviderChoices,
     standard_params: StandardParams,
     extra_params: ExtraParams,
 ) -> OBBject[BaseModel]:
-    """Futures EOD Price."""
+    """Futures Historical Price."""
     return OBBject(results=Query(**locals()).execute())
 
 
@@ -31,5 +31,5 @@ def curve(
     standard_params: StandardParams,
     extra_params: ExtraParams,
 ) -> OBBject[BaseModel]:
-    """Futures EOD Price."""
+    """Futures Historical Price."""
     return OBBject(results=Query(**locals()).execute())
diff --git a/openbb_sdk/extensions/stocks/openbb_stocks/stocks_router.py b/openbb_sdk/extensions/stocks/openbb_stocks/stocks_router.py
index a0eca454dba..2783143315c 100644
--- a/openbb_sdk/extensions/stocks/openbb_stocks/stocks_router.py
+++ b/openbb_sdk/extensions/stocks/openbb_stocks/stocks_router.py
@@ -35,7 +35,7 @@ router.include_router(options_router)
 # router.include_router(ins_router)
 
 
-@router.command(model="StockEOD")
+@router.command(model="StockHistorical")
 def load(
     cc: CommandContext,
     provider_choices: ProviderChoices,
diff --git a/openbb_sdk/openbb/package/__extensions__.py b/openbb_sdk/openbb/package/__extensions__.py
index f7de27006cf..b72edde1849 100644
--- a/openbb_sdk/openbb/package/__extensions__.py
+++ b/openbb_sdk/openbb/package/__extensions__.py
@@ -10,8 +10,11 @@ class Extensions(Container):
     /economy
     /fixedincome
     /forex
+    /futures
     /news
+    /qa
     /stocks
+    /ta
     """
 
     def __repr__(self) -> str:
@@ -41,14 +44,32 @@ class Extensions(Container):
 
         return forex.CLASS_forex(command_runner=self._command_runner)
 
+    @property
+    def futures(self):  # route = "/futures"
+        from . import futures
+
+        return futures.CLASS_futures(command_runner=self._command_runner)
+
     @property
     def news(self):  # route = "/news"
         from . import news
 
         return news.CLASS_news(command_runner=self._command_runner)
 
+    @property
+    def qa(self):  # route = "/qa"
+        from . import qa
+
+        return qa.CLASS_qa(command_runner=self._command_runner)
+
     @property
     def stocks(self):  # route = "/stocks"
         from . import stocks
 
         return stocks.CLASS_stocks(command_runner=self._command_runner)
+
+    @property
+    def ta(self):  # route = "/ta"
+        from . import ta
+
+        return ta.CLASS_ta(command_runner=self._command_runner)
diff --git a/openbb_sdk/openbb/package/crypto.py b/openbb_sdk/openbb/package/crypto.py
index e36cf43bb3d..8a5574dd000 100644
--- a/openbb_sdk/openbb/package/crypto.py
+++ b/openbb_sdk/openbb/package/crypto.py
@@ -1,14 +1,14 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
 import datetime
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_crypto(Container):
@@ -22,27 +22,26 @@ class CLASS_crypto(Container):
     @validate_arguments
     def load(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[Literal["fmp", "polygon", "yfinance"]] = None,
         **kwargs
     ) -> OBBject[List]:
-        """Crypto EOD Price.
+        """Crypto Historical Price.
 
         Parameters
         ----------
@@ -52,13 +51,11 @@ class CLASS_crypto(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['fmp', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
-        timeseries : Union[pydantic.types.NonNegativeInt, NoneType]
+        timeseries : Optional[pydantic.types.NonNegativeInt]
             Number of days to look back. (provider: fmp)
         timespan : Literal['minute', 'hour', 'day', 'week', 'month', 'quarter', 'year']
             Timespan of the data. (provider: polygon)
@@ -70,13 +67,23 @@ class CLASS_crypto(Container):
             Whether the data is adjusted. (provider: polygon)
         multiplier : PositiveInt
             Multiplier of the timespan. (provider: polygon)
+        interval : Optional[Literal['1m', '2m', '5m', '15m', '30m', '60m', '90m', '1h', '1d', '5d', '1wk', '1mo', '3mo']]
+            Data granularity. (provider: yfinance)
+        period : Optional[Literal['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']]
+            Period of the data to return. (provider: yfinance)
+        prepost : bool
+            Include Pre and Post market data. (provider: yfinance)
+        adjust : bool
+            Adjust all the data automatically. (provider: yfinance)
+        back_adjust : bool
+            Back-adjusted data to mimic true historical prices. (provider: yfinance)
 
         Returns
         -------
         OBBject
-            results : List[CryptoEOD]
+            results : List[CryptoHistorical]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['fmp', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -85,8 +92,8 @@ class CLASS_crypto(Container):
             metadata: Optional[Metadata]
                 Metadata info about the command execution.
 
-        CryptoEOD
-        ---------
+        CryptoHistorical
+        ----------------
         date : Optional[datetime]
             The date of the data.
         open : Optional[PositiveFloat]
@@ -127,7 +134,6 @@ class CLASS_crypto(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/economy.py b/openbb_sdk/openbb/package/economy.py
index b8a6d0a8720..30c962f2726 100644
--- a/openbb_sdk/openbb/package/economy.py
+++ b/openbb_sdk/openbb/package/economy.py
@@ -1,14 +1,14 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
 import datetime
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_economy(Container):
@@ -16,6 +16,8 @@ class CLASS_economy(Container):
     available_indices
     const
     cpi
+    european_index
+    european_index_constituents
     index
     risk
     """
@@ -25,28 +27,25 @@ class CLASS_economy(Container):
 
     @validate_arguments
     def available_indices(
-        self,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
-        **kwargs
+        self, provider: Optional[Literal["cboe", "fmp", "yfinance"]] = None, **kwargs
     ) -> OBBject[List]:
-        """AVAILABLE_INDICES.
+        """Lists of available indices from a provider.
 
         Parameters
         ----------
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['cboe', 'fmp', 'yfinance']]
             The provider to use for the query, by default None.
-            If None, the provider specified in defaults is selected or 'fmp' if there is
+            If None, the provider specified in defaults is selected or 'cboe' if there is
             no default.
+        europe : bool
+            Filter for European indices. False for US indices. (provider: cboe)
 
         Returns
         -------
         OBBject
             results : List[AvailableIndices]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['cboe', 'fmp', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -57,16 +56,38 @@ class CLASS_economy(Container):
 
         AvailableIndices
         ----------------
-        symbol : Optional[str]
-            Symbol to get data for.
         name : Optional[str]
             Name of the index.
         currency : Optional[str]
             Currency the index is traded in.
+        isin : Optional[str]
+            ISIN code for the index. Valid only for European indices. (provider: cboe)
+        region : Optional[str]
+            Region for the index. Valid only for European indices (provider: cboe)
+        symbol : Optional[str]
+            Symbol for the index. (provider: cboe)
+        description : Optional[str]
+            Description for the index. Valid only for US indices. (provider: cboe)
+        data_delay : Optional[int]
+            Data delay for the index. Valid only for US indices. (provider: cboe)
+        open_time : Optional[time]
+            Opening time for the index. Valid only for US indices. (provider: cboe)
+        close_time : Optional[time]
+            Closing time for the index. Valid only for US indices. (provider: cboe)
+        time_zone : Optional[str]
+            Time zone for the index. Valid only for US indices. (provider: cboe)
+        tick_days : Optional[str]
+            The trading days for the index. Valid only for US indices. (provider: cboe)
+        tick_frequency : Optional[str]
+            The frequency of the index ticks. Valid only for US indices. (provider: cboe)
+        tick_period : Optional[str]
+            The period of the index ticks. Valid only for US indices. (provider: cboe)
         stock_exchange : Optional[str]
-            Stock exchange where the index is listed.
+            Stock exchange where the index is listed. (provider: fmp)
         exchange_short_name : Optional[str]
-            Short name of the stock exchange where the index is listed."""  # noqa: E501
+            Short name of the stock exchange where the index is listed. (provider: fmp)
+        code : Optional[str]
+            ID code for keying the index in the OpenBB Terminal. (provider: yfinance)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -74,7 +95,6 @@ class CLASS_economy(Container):
             },
             standard_params={},
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -85,14 +105,13 @@ class CLASS_economy(Container):
     @validate_arguments
     def const(
         self,
-        index: typing_extensions.Annotated[
+        index: Annotated[
             Literal["nasdaq", "sp500", "dowjones"],
             OpenBBCustomParameter(
                 description="Index for which we want to fetch the constituents."
             ),
         ] = "dowjones",
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Get the constituents of an index.
@@ -101,9 +120,7 @@ class CLASS_economy(Container):
         ----------
         index : Literal['nasdaq', 'sp500', 'dowjones']
             Index for which we want to fetch the constituents.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -113,7 +130,7 @@ class CLASS_economy(Container):
         OBBject
             results : List[MajorIndicesConstituents]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -149,7 +166,6 @@ class CLASS_economy(Container):
                 "index": index,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -160,7 +176,7 @@ class CLASS_economy(Container):
     @validate_arguments
     def cpi(
         self,
-        countries: typing_extensions.Annotated[
+        countries: Annotated[
             List[
                 Literal[
                     "australia",
@@ -216,34 +232,33 @@ class CLASS_economy(Container):
             ],
             OpenBBCustomParameter(description="The country or countries to get data."),
         ],
-        units: typing_extensions.Annotated[
+        units: Annotated[
             Literal["growth_previous", "growth_same", "index_2015"],
             OpenBBCustomParameter(description="The data units."),
         ] = "growth_same",
-        frequency: typing_extensions.Annotated[
+        frequency: Annotated[
             Literal["monthly", "quarter", "annual"],
             OpenBBCustomParameter(description="The data time frequency."),
         ] = "monthly",
-        harmonized: typing_extensions.Annotated[
+        harmonized: Annotated[
             bool,
             OpenBBCustomParameter(
                 description="Whether you wish to obtain harmonized data."
             ),
         ] = False,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """CPI.
@@ -262,9 +277,7 @@ class CLASS_economy(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -274,7 +287,7 @@ class CLASS_economy(Container):
         OBBject
             results : List[CPI]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -307,7 +320,6 @@ class CLASS_economy(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -316,29 +328,28 @@ class CLASS_economy(Container):
         )
 
     @validate_arguments
-    def index(
+    def european_index(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[Literal["cboe"]] = None,
         **kwargs
     ) -> OBBject[List]:
-        """Get OHLCV data for an index.
+        """Get historical close values for select European indices.
 
         Parameters
         ----------
@@ -348,16 +359,182 @@ class CLASS_economy(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['cboe']]
             The provider to use for the query, by default None.
-            If None, the provider specified in defaults is selected or 'fmp' if there is
+            If None, the provider specified in defaults is selected or 'cboe' if there is
             no default.
-        timeseries : Union[pydantic.types.NonNegativeInt, NoneType]
+        interval : Optional[Literal['1d', '1m']]
+            Use interval, 1m, for intraday prices during the most recent trading period. (provider: cboe)
+
+        Returns
+        -------
+        OBBject
+            results : List[EuropeanIndexHistorical]
+                Serializable results.
+            provider : Optional[Literal['cboe']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        EuropeanIndexHistorical
+        -----------------------
+        date : Union[date, datetime]
+            The date of the data.
+        close : Optional[float]
+            The close price of the symbol.
+        open : Optional[float]
+            Opening price for the interval. Only valid when interval is 1m. (provider: cboe)
+        high : Optional[float]
+            High price for the interval. Only valid when interval is 1m. (provider: cboe)
+        low : Optional[float]
+            Low price for the interval. Only valid when interval is 1m. (provider: cboe)
+        utc_datetime : Optional[datetime]
+            UTC datetime. Only valid when interval is 1m. (provider: cboe)"""  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
+                "start_date": start_date,
+                "end_date": end_date,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/economy/european_index",
+            **inputs,
+        )
+
+    @validate_arguments
+    def european_index_constituents(
+        self,
+        symbol: Annotated[
+            Union[str, List[str]],
+            OpenBBCustomParameter(description="Symbol to get data for."),
+        ],
+        provider: Optional[Literal["cboe"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Get  current levels for constituents of select European indices.
+
+        Parameters
+        ----------
+        symbol : Union[str, List[str]]
+            Symbol to get data for.
+        provider : Optional[Literal['cboe']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'cboe' if there is
+            no default.
+
+        Returns
+        -------
+        OBBject
+            results : List[EuropeanIndexConstituents]
+                Serializable results.
+            provider : Optional[Literal['cboe']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        EuropeanIndexConstituents
+        -------------------------
+        symbol : Optional[str]
+            Symbol of the constituent company in the index.
+        price : Optional[float]
+            Current price of the constituent company in the index.
+        open : Optional[float]
+            The open price of the symbol.
+        high : Optional[float]
+            The high price of the symbol.
+        low : Optional[float]
+            The low price of the symbol.
+        close : Optional[float]
+            The close price of the symbol.
+        volume : Optional[float]
+            The volume of the symbol.
+        prev_close : Optional[float]
+            Previous closing  price. (provider: cboe)
+        change : Optional[float]
+            Change in price. (provider: cboe)
+        change_percent : Optional[float]
+            Change in price as a percentage. (provider: cboe)
+        tick : Optional[str]
+            Whether the last sale was an up or down tick. (provider: cboe)
+        last_trade_timestamp : Optional[datetime]
+            Last trade timestamp for the symbol. (provider: cboe)
+        exchange_id : Optional[int]
+            The Exchange ID number. (provider: cboe)
+        seqno : Optional[int]
+            Sequence number of the last trade on the tape. (provider: cboe)
+        asset_type : Optional[str]
+            Type of asset. (provider: cboe)"""  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/economy/european_index_constituents",
+            **inputs,
+        )
+
+    @validate_arguments
+    def index(
+        self,
+        symbol: Annotated[
+            Union[str, List[str]],
+            OpenBBCustomParameter(description="Symbol to get data for."),
+        ],
+        start_date: Annotated[
+            Union[datetime.date, None, str],
+            OpenBBCustomParameter(
+                description="Start date of the data, in YYYY-MM-DD format."
+            ),
+        ] = None,
+        end_date: Annotated[
+            Union[datetime.date, None, str],
+            OpenBBCustomParameter(
+                description="End date of the data, in YYYY-MM-DD format."
+            ),
+        ] = None,
+        provider: Optional[Literal["cboe", "fmp", "polygon", "yfinance"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Get historical  levels for an index.
+
+        Parameters
+        ----------
+        symbol : Union[str, List[str]]
+            Symbol to get data for.
+        start_date : Union[datetime.date, NoneType, str]
+            Start date of the data, in YYYY-MM-DD format.
+        end_date : Union[datetime.date, NoneType, str]
+            End date of the data, in YYYY-MM-DD format.
+        provider : Optional[Literal['cboe', 'fmp', 'polygon', 'yfinance']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'cboe' if there is
+            no default.
+        interval : Union[Literal['1d', '1m'], NoneType, Literal['1min', '5min', '15min', '30min', '1hour', '4hour', '1day'], Literal['1m', '2m', '5m', '15m', '30m', '60m', '90m', '1h', '1d', '5d', '1wk', '1mo', '3mo']]
+            None
+        timeseries : Optional[pydantic.types.NonNegativeInt]
             Number of days to look back. (provider: fmp)
-        interval : Literal['1min', '5min', '15min', '30min', '1hour', '4hour', '1day']
-            Interval of the data to fetch. (provider: fmp)
         timespan : Literal['minute', 'hour', 'day', 'week', 'month', 'quarter', 'year']
             Timespan of the data. (provider: polygon)
         sort : Literal['asc', 'desc']
@@ -368,13 +545,21 @@ class CLASS_economy(Container):
             Whether the data is adjusted. (provider: polygon)
         multiplier : PositiveInt
             Multiplier of the timespan. (provider: polygon)
+        period : Optional[Literal['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']]
+            Period of the data to return. (provider: yfinance)
+        prepost : bool
+            Include Pre and Post market data. (provider: yfinance)
+        adjust : bool
+            Adjust all the data automatically. (provider: yfinance)
+        back_adjust : bool
+            Back-adjusted data to mimic true historical prices. (provider: yfinance)
 
         Returns
         -------
         OBBject
-            results : List[MajorIndicesEOD]
+            results : List[MajorIndicesHistorical]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['cboe', 'fmp', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -383,8 +568,8 @@ class CLASS_economy(Container):
             metadata: Optional[Metadata]
                 Metadata info about the command execution.
 
-        MajorIndicesEOD
-        ---------------
+        MajorIndicesHistorical
+        ----------------------
         date : Optional[datetime]
             The date of the data.
         open : Optional[PositiveFloat]
@@ -395,10 +580,14 @@ class CLASS_economy(Container):
             The low price of the symbol.
         close : Optional[PositiveFloat]
             The close price of the symbol.
-        volume : Optional[float]
+        volume : Optional[NonNegativeInt]
             The volume of the symbol.
-        vwap : Optional[float]
-            Volume Weighted Average Price of the symbol.
+        calls_volume : Optional[float]
+            Number of calls traded during the most recent trading period. Only valid if interval is 1m. (provider: cboe)
+        puts_volume : Optional[float]
+            Number of puts traded during the most recent trading period. Only valid if interval is 1m. (provider: cboe)
+        total_options_volume : Optional[float]
+            Total number of options traded during the most recent trading period. Only valid if interval is 1m. (provider: cboe)
         adj_close : Optional[float]
             Adjusted Close Price of the symbol. (provider: fmp)
         unadjusted_volume : Optional[float]
@@ -411,8 +600,6 @@ class CLASS_economy(Container):
             Human readable format of the date. (provider: fmp)
         change_over_time : Optional[float]
             Change \\% in the price of the symbol over a period of time. (provider: fmp)
-        n : Optional[PositiveInt]
-            Number of transactions for the symbol in the time period. (provider: polygon)
         """  # noqa: E501
 
         inputs = filter_inputs(
@@ -425,7 +612,6 @@ class CLASS_economy(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -435,18 +621,13 @@ class CLASS_economy(Container):
 
     @validate_arguments
     def risk(
-        self,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
-        **kwargs
+        self, provider: Optional[Literal["fmp"]] = None, **kwargs
     ) -> OBBject[List]:
         """Market Risk Premium.
 
         Parameters
         ----------
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -456,7 +637,7 @@ class CLASS_economy(Container):
         OBBject
             results : List[RiskPremium]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -482,7 +663,6 @@ class CLASS_economy(Container):
             },
             standard_params={},
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/extension_map.json b/openbb_sdk/openbb/package/extension_map.json
index 508b6e9bfa8..bfff08afd9a 100644
--- a/openbb_sdk/openbb/package/extension_map.json
+++ b/openbb_sdk/openbb/package/extension_map.json
@@ -4,13 +4,22 @@
         "economy@0.1.0",
         "fixedincome@0.1.0",
         "forex@0.1.0",
+        "futures@0.1.0",
         "news@0.1.0",
-        "stocks@0.1.0"
+        "openbb_charting@0.1.0",
+        "qa@0.1.0",
+        "stocks@0.1.0",
+        "ta@0.1.0"
     ],
     "openbb_provider_extension": [
+        "alpha_vantage@0.1.0",
         "benzinga@0.1.0",
+        "cboe@0.1.0",
         "fmp@0.1.0",
         "fred@0.1.0",
-        "polygon@0.1.0"
+        "intrinio@0.1.0",
+        "polygon@0.1.0",
+        "quandl@0.1.0",
+        "yfinance@0.1.0"
     ]
 }
\ No newline at end of file
diff --git a/openbb_sdk/openbb/package/fixedincome.py b/openbb_sdk/openbb/package/fixedincome.py
index 51bbcd86225..c1854d40f13 100644
--- a/openbb_sdk/openbb/package/fixedincome.py
+++ b/openbb_sdk/openbb/package/fixedincome.py
@@ -1,14 +1,14 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
 import datetime
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_fixedincome(Container):
@@ -30,20 +30,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def ameribor(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """
@@ -57,9 +56,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -71,7 +68,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[AMERIBOR]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -96,7 +93,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -107,20 +103,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def estr(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """
@@ -135,9 +130,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -149,7 +142,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[ESTR]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -174,7 +167,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -185,20 +177,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def fed(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """
@@ -213,9 +204,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -227,7 +216,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[FEDFUNDS]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -252,7 +241,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -263,20 +251,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def iorb(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """
@@ -291,9 +278,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -303,7 +288,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[IORB]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -328,7 +313,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -338,10 +322,7 @@ class CLASS_fixedincome(Container):
 
     @validate_arguments
     def projections(
-        self,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
-        **kwargs
+        self, provider: Optional[Literal["fred"]] = None, **kwargs
     ) -> OBBject[List]:
         """
             Get Effective Federal Funds Rate data. A bank rate is the interest rate a nation's central bank charges to its
@@ -351,9 +332,7 @@ class CLASS_fixedincome(Container):
 
         Parameters
         ----------
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -365,7 +344,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[PROJECTIONS]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -399,7 +378,6 @@ class CLASS_fixedincome(Container):
             },
             standard_params={},
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -410,20 +388,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def sofr(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Get United States yield curve.
@@ -434,9 +411,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -448,7 +423,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[SOFR]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -473,7 +448,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -484,20 +458,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def sonia(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """
@@ -511,9 +484,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -525,7 +496,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[SONIA]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -550,7 +521,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -561,20 +531,19 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def treasury(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Get treasury rates.
@@ -585,9 +554,7 @@ class CLASS_fixedincome(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -597,7 +564,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[TreasuryRates]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -644,7 +611,6 @@ class CLASS_fixedincome(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -655,31 +621,28 @@ class CLASS_fixedincome(Container):
     @validate_arguments
     def ycrv(
         self,
-        date: typing_extensions.Annotated[
-            Union[datetime.date, None],
+        date: Annotated[
+            Optional[datetime.date],
             OpenBBCustomParameter(
                 description="Date to get Yield Curve data.  Defaults to the most recent FRED entry."
             ),
         ] = None,
-        inflation_adjusted: typing_extensions.Annotated[
-            Union[bool, None],
+        inflation_adjusted: Annotated[
+            Optional[bool],
             OpenBBCustomParameter(description="Get inflation adjusted rates."),
         ] = False,
-        chart: bool = False,
-        provider: Union[Literal["fred"], None] = None,
+        provider: Optional[Literal["fred"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Get United States yield curve.
 
         Parameters
         ----------
-        date : Union[datetime.date, NoneType]
+        date : Optional[datetime.date]
             Date to get Yield Curve data.  Defaults to the most recent FRED entry.
-        inflation_adjusted : Union[bool, NoneType]
+        inflation_adjusted : Optional[bool]
             Get inflation adjusted rates.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fred'], NoneType]
+        provider : Optional[Literal['fred']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fred' if there is
             no default.
@@ -689,7 +652,7 @@ class CLASS_fixedincome(Container):
         OBBject
             results : List[USYieldCurve]
                 Serializable results.
-            provider : Union[Literal['fred'], NoneType]
+            provider : Optional[Literal['fred']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -714,7 +677,6 @@ class CLASS_fixedincome(Container):
                 "inflation_adjusted": inflation_adjusted,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/forex.py b/openbb_sdk/openbb/package/forex.py
index d40e096f622..8f065eba540 100644
--- a/openbb_sdk/openbb/package/forex.py
+++ b/openbb_sdk/openbb/package/forex.py
@@ -1,14 +1,14 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
 import datetime
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_forex(Container):
@@ -23,24 +23,23 @@ class CLASS_forex(Container):
     @validate_arguments
     def load(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[Literal["fmp", "polygon", "yfinance"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Forex Intraday Price.
@@ -53,9 +52,7 @@ class CLASS_forex(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['fmp', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -69,13 +66,23 @@ class CLASS_forex(Container):
             Whether the data is adjusted. (provider: polygon)
         multiplier : PositiveInt
             Multiplier of the timespan. (provider: polygon)
+        interval : Optional[Literal['1m', '2m', '5m', '15m', '30m', '60m', '90m', '1h', '1d', '5d', '1wk', '1mo', '3mo']]
+            Data granularity. (provider: yfinance)
+        period : Optional[Literal['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']]
+            Period of the data to return. (provider: yfinance)
+        prepost : bool
+            Include Pre and Post market data. (provider: yfinance)
+        adjust : bool
+            Adjust all the data automatically. (provider: yfinance)
+        back_adjust : bool
+            Back-adjusted data to mimic true historical prices. (provider: yfinance)
 
         Returns
         -------
         OBBject
-            results : List[ForexEOD]
+            results : List[ForexHistorical]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['fmp', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -84,8 +91,8 @@ class CLASS_forex(Container):
             metadata: Optional[Metadata]
                 Metadata info about the command execution.
 
-        ForexEOD
-        --------
+        ForexHistorical
+        ---------------
         date : Optional[datetime]
             The date of the data.
         open : Optional[PositiveFloat]
@@ -126,7 +133,6 @@ class CLASS_forex(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -136,34 +142,29 @@ class CLASS_forex(Container):
 
     @validate_arguments
     def pairs(
-        self,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
-        **kwargs
+        self, provider: Optional[Literal["fmp", "intrinio", "polygon"]] = None, **kwargs
     ) -> OBBject[List]:
         """Forex Available Pairs.
 
         Parameters
         ----------
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['fmp', 'intrinio', 'polygon']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
-        symbol : Union[str, NoneType]
+        symbol : Optional[str]
             Symbol of the pair to search. (provider: polygon)
-        date : Union[datetime.date, NoneType]
+        date : Optional[datetime.date]
             A specific date to get data for. (provider: polygon)
-        search : Union[str, NoneType]
+        search : Optional[str]
             Search for terms within the ticker and/or company name. (provider: polygon)
-        active : Union[Literal[True, False], NoneType]
+        active : Optional[Literal[True, False]]
             Specify if the tickers returned should be actively traded on the queried date. (provider: polygon)
-        order : Union[Literal['asc', 'desc'], NoneType]
+        order : Optional[Literal['asc', 'desc']]
             Order data by ascending or descending. (provider: polygon)
-        sort : Union[Literal['ticker', 'name', 'market', 'locale', 'currency_symbol', 'currency_name', 'base_currency_symbol', 'base_currency_name', 'last_updated_utc', 'delisted_utc'], NoneType]
+        sort : Optional[Literal['ticker', 'name', 'market', 'locale', 'currency_symbol', 'currency_name', 'base_currency_symbol', 'base_currency_name', 'last_updated_utc', 'delisted_utc']]
             Sort field used for ordering. (provider: polygon)
-        limit : Union[pydantic.types.PositiveInt, NoneType]
+        limit : Optional[pydantic.types.PositiveInt]
             The number of data entries to return. (provider: polygon)
 
         Returns
@@ -171,7 +172,7 @@ class CLASS_forex(Container):
         OBBject
             results : List[ForexPairs]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['fmp', 'intrinio', 'polygon']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -192,6 +193,12 @@ class CLASS_forex(Container):
             Stock exchange of the currency pair. (provider: fmp)
         exchange_short_name : Optional[str]
             Short name of the stock exchange of the currency pair. (provider: fmp)
+        code : Optional[str]
+            Code of the currency pair. (provider: intrinio)
+        base_currency : Optional[str]
+            ISO 4217 currency code of the base currency. (provider: intrinio)
+        quote_currency : Optional[str]
+            ISO 4217 currency code of the quote currency. (provider: intrinio)
         market : Optional[str]
             The name of the trading market. Always 'fx'. (provider: polygon)
         locale : Optional[str]
@@ -215,7 +222,6 @@ class CLASS_forex(Container):
             },
             standard_params={},
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/futures.py b/openbb_sdk/openbb/package/futures.py
new file mode 100644
index 00000000000..b5ffdb711e7
--- /dev/null
+++ b/openbb_sdk/openbb/package/futures.py
@@ -0,0 +1,187 @@
+### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
+
+import datetime
+from typing import List, Literal, Optional, Union
+
+from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
+from openbb_core.app.model.obbject import OBBject
+from openbb_core.app.static.container import Container
+from openbb_core.app.static.filters import filter_inputs
+from pydantic import validate_arguments
+from typing_extensions import Annotated
+
+
+class CLASS_futures(Container):
+    """/futures
+    curve
+    load
+    """
+
+    def __repr__(self) -> str:
+        return self.__doc__ or ""
+
+    @validate_arguments
+    def curve(
+        self,
+        symbol: Annotated[
+            Union[str, List[str]],
+            OpenBBCustomParameter(description="Symbol to get data for."),
+        ],
+        date: Annotated[
+            Optional[datetime.date],
+            OpenBBCustomParameter(description="Historical date to search curve for."),
+        ] = None,
+        provider: Optional[Literal["cboe", "yfinance"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Futures Historical Price.
+
+        Parameters
+        ----------
+        symbol : Union[str, List[str]]
+            Symbol to get data for.
+        date : Optional[datetime.date]
+            Historical date to search curve for.
+        provider : Optional[Literal['cboe', 'yfinance']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'cboe' if there is
+            no default.
+
+        Returns
+        -------
+        OBBject
+            results : List[FuturesCurve]
+                Serializable results.
+            provider : Optional[Literal['cboe', 'yfinance']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        FuturesCurve
+        ------------
+        expiration : Optional[str]
+            Futures expiration month.
+        price : Optional[float]
+            The close price of the symbol.
+        symbol : Optional[str]
+            The trading symbol for the tenor of future. (provider: cboe)"""  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
+                "date": date,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/futures/curve",
+            **inputs,
+        )
+
+    @validate_arguments
+    def load(
+        self,
+        symbol: Annotated[
+            Union[str, List[str]],
+            OpenBBCustomParameter(description="Symbol to get data for."),
+        ],
+        start_date: Annotated[
+            Union[datetime.date, None, str],
+            OpenBBCustomParameter(
+                description="Start date of the data, in YYYY-MM-DD format."
+            ),
+        ] = None,
+        end_date: Annotated[
+            Union[datetime.date, None, str],
+            OpenBBCustomParameter(
+                description="End date of the data, in YYYY-MM-DD format."
+            ),
+        ] = None,
+        expiration: Annotated[
+            Optional[str],
+            OpenBBCustomParameter(description="Future expiry date with format YYYY-MM"),
+        ] = None,
+        provider: Optional[Literal["yfinance"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Futures Historical Price.
+
+        Parameters
+        ----------
+        symbol : Union[str, List[str]]
+            Symbol to get data for.
+        start_date : Union[datetime.date, NoneType, str]
+            Start date of the data, in YYYY-MM-DD format.
+        end_date : Union[datetime.date, NoneType, str]
+            End date of the data, in YYYY-MM-DD format.
+        expiration : Optional[str]
+            Future expiry date with format YYYY-MM
+        provider : Optional[Literal['yfinance']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'yfinance' if there is
+            no default.
+        interval : Optional[Literal['1m', '2m', '5m', '15m', '30m', '60m', '90m', '1h', '1d', '5d', '1wk', '1mo', '3mo']]
+            Data granularity. (provider: yfinance)
+        period : Optional[Literal['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']]
+            Period of the data to return. (provider: yfinance)
+        prepost : bool
+            Include Pre and Post market data. (provider: yfinance)
+        adjust : bool
+            Adjust all the data automatically. (provider: yfinance)
+        back_adjust : bool
+            Back-adjusted data to mimic true historical prices. (provider: yfinance)
+
+        Returns
+        -------
+        OBBject
+            results : List[FuturesHistorical]
+                Serializable results.
+            provider : Optional[Literal['yfinance']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        FuturesHistorical
+        -----------------
+        date : Optional[datetime]
+            The date of the data.
+        open : Optional[float]
+            The open price of the symbol.
+        high : Optional[float]
+            The high price of the symbol.
+        low : Optional[float]
+            The low price of the symbol.
+        close : Optional[float]
+            The close price of the symbol.
+        volume : Optional[float]
+            The volume of the symbol."""  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
+                "start_date": start_date,
+                "end_date": end_date,
+                "expiration": expiration,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/futures/load",
+            **inputs,
+        )
diff --git a/openbb_sdk/openbb/package/module_map.json b/openbb_sdk/openbb/package/module_map.json
index baff015a4b9..a75cc7694c9 100644
--- a/openbb_sdk/openbb/package/module_map.json
+++ b/openbb_sdk/openbb/package/module_map.json
@@ -6,6 +6,8 @@
     "economy_available_indices": "/economy/available_indices",
     "economy_const": "/economy/const",
     "economy_cpi": "/economy/cpi",
+    "economy_european_index": "/economy/european_index",
+    "economy_european_index_constituents": "/economy/european_index_constituents",
     "economy_index": "/economy/index",
     "economy_risk": "/economy/risk",
     "fixedincome": "/fixedincome",
@@ -21,8 +23,22 @@
     "forex": "/forex",
     "forex_load": "/forex/load",
     "forex_pairs": "/forex/pairs",
+    "futures": "/futures",
+    "futures_curve": "/futures/curve",
+    "futures_load": "/futures/load",
     "news": "/news",
     "news_globalnews": "/news/globalnews",
+    "qa": "/qa",
+    "qa_capm": "/qa/capm",
+    "qa_kurtosis": "/qa/kurtosis",
+    "qa_normality": "/qa/normality",
+    "qa_om": "/qa/om",
+    "qa_quantile": "/qa/quantile",
+    "qa_sh": "/qa/sh",
+    "qa_skew": "/qa/skew",
+    "qa_so": "/qa/so",
+    "qa_summary": "/qa/summary",
+    "qa_unitroot": "/qa/unitroot",
     "stocks": "/stocks",
     "stocks_ca": "/stocks/ca",
     "stocks_ca_peers": "/stocks/ca/peers",
@@ -56,8 +72,39 @@
     "stocks_fa_shrs": "/stocks/fa/shrs",
     "stocks_fa_split": "/stocks/fa/split",
     "stocks_fa_transcript": "/stocks/fa/transcript",
+    "stocks_info": "/stocks/info",
     "stocks_load": "/stocks/load",
     "stocks_multiples": "/stocks/multiples",
     "stocks_news": "/stocks/news",
-    "stocks_quote": "/stocks/quote"
+    "stocks_options": "/stocks/options",
+    "stocks_options_chains": "/stocks/options/chains",
+    "stocks_quote": "/stocks/quote",
+    "stocks_search": "/stocks/search",
+    "ta": "/ta",
+    "ta_ad": "/ta/ad",
+    "ta_adosc": "/ta/adosc",
+    "ta_adx": "/ta/adx",
+    "ta_aroon": "/ta/aroon",
+    "ta_atr": "/ta/atr",
+    "ta_bbands": "/ta/bbands",
+    "ta_cci": "/ta/cci",
+    "ta_cg": "/ta/cg",
+    "ta_clenow": "/ta/clenow",
+    "ta_cones": "/ta/cones",
+    "ta_demark": "/ta/demark",
+    "ta_donchian": "/ta/donchian",
+    "ta_ema": "/ta/ema",
+    "ta_fib": "/ta/fib",
+    "ta_fisher": "/ta/fisher",
+    "ta_hma": "/ta/hma",
+    "ta_ichimoku": "/ta/ichimoku",
+    "ta_kc": "/ta/kc",
+    "ta_macd": "/ta/macd",
+    "ta_obv": "/ta/obv",
+    "ta_rsi": "/ta/rsi",
+    "ta_sma": "/ta/sma",
+    "ta_stoch": "/ta/stoch",
+    "ta_vwap": "/ta/vwap",
+    "ta_wma": "/ta/wma",
+    "ta_zlma": "/ta/zlma"
 }
\ No newline at end of file
diff --git a/openbb_sdk/openbb/package/news.py b/openbb_sdk/openbb/package/news.py
index 675b4abfaa6..3e72297931b 100644
--- a/openbb_sdk/openbb/package/news.py
+++ b/openbb_sdk/openbb/package/news.py
@@ -1,14 +1,14 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
-from typing import List, Literal, Union
+from typing import List, Literal, Optional
 
 import pydantic
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_news(Container):
@@ -22,12 +22,11 @@ class CLASS_news(Container):
     @validate_arguments
     def globalnews(
         self,
-        page: typing_extensions.Annotated[
+        page: Annotated[
             pydantic.types.NonNegativeInt,
             OpenBBCustomParameter(description="Page of the global news."),
         ] = 0,
-        chart: bool = False,
-        provider: Union[Literal["benzinga", "fmp"], None] = None,
+        provider: Optional[Literal["benzinga", "fmp", "intrinio"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Global News.
@@ -36,9 +35,7 @@ class CLASS_news(Container):
         ----------
         page : NonNegativeInt
             Page of the global news.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['benzinga', 'fmp'], NoneType]
+        provider : Optional[Literal['benzinga', 'fmp', 'intrinio']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'benzinga' if there is
             no default.
@@ -46,39 +43,45 @@ class CLASS_news(Container):
             Number of results to return per page. (provider: benzinga)
         display_output : Literal['headline', 'summary', 'full', 'all']
             Type of data to return. (provider: benzinga)
-        date : Union[datetime.datetime, NoneType]
+        date : Optional[datetime.datetime]
             Date of the news to retrieve. (provider: benzinga)
-        date_from : Union[datetime.datetime, NoneType]
+        date_from : Optional[datetime.datetime]
             Start date of the news to retrieve. (provider: benzinga)
-        date_to : Union[datetime.datetime, NoneType]
+        date_to : Optional[datetime.datetime]
             End date of the news to retrieve. (provider: benzinga)
-        updated_since : Union[int, NoneType]
+        updated_since : Optional[int]
             Number of seconds since the news was updated. (provider: benzinga)
-        published_since : Union[int, NoneType]
+        published_since : Optional[int]
             Number of seconds since the news was published. (provider: benzinga)
-        sort : Union[Literal['published_at', 'updated_at', 'title', 'author', 'channel', 'ticker', 'topic', 'content_type'], NoneType]
+        sort : Optional[Literal['published_at', 'updated_at', 'title', 'author', 'channel', 'ticker', 'topic', 'content_type']]
             Order in which to sort the news.  (provider: benzinga)
-        isin : Union[str, NoneType]
+        isin : Optional[str]
             The ISIN of the news to retrieve. (provider: benzinga)
-        cusip : Union[str, NoneType]
+        cusip : Optional[str]
             The CUSIP of the news to retrieve. (provider: benzinga)
-        tickers : Union[str, NoneType]
+        tickers : Optional[str]
             Tickers of the news to retrieve. (provider: benzinga)
-        channels : Union[str, NoneType]
+        channels : Optional[str]
             Channels of the news to retrieve. (provider: benzinga)
-        topics : Union[str, NoneType]
+        topics : Optional[str]
             Topics of the news to retrieve. (provider: benzinga)
-        authors : Union[str, NoneType]
+        authors : Optional[str]
             Authors of the news to retrieve. (provider: benzinga)
-        content_types : Union[str, NoneType]
+        content_types : Optional[str]
             Content types of the news to retrieve. (provider: benzinga)
+        next_page : str
+            Token to get the next page of data from a previous API call. (provider: intrinio)
+        limit : Optional[int]
+            The number of data entries to return. (provider: intrinio)
+        all_pages : Optional[bool]
+            Returns all pages of data from the API call at once. (provider: intrinio)
 
         Returns
         -------
         OBBject
             results : List[GlobalNews]
                 Serializable results.
-            provider : Union[Literal['benzinga', 'fmp'], NoneType]
+            provider : Optional[Literal['benzinga', 'fmp', 'intrinio']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -108,7 +111,11 @@ class CLASS_news(Container):
         teaser : Optional[str]
             Teaser of the news. (provider: benzinga)
         site : Optional[str]
-            Site of the news. (provider: fmp)"""  # noqa: E501
+            Site of the news. (provider: fmp)
+        id : Optional[str]
+            Intrinio ID for the news article. (provider: intrinio)
+        company : Optional[Mapping[str, Any]]
+            Company details related to the news article. (provider: intrinio)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -118,7 +125,6 @@ class CLASS_news(Container):
                 "page": page,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/qa.py b/openbb_sdk/openbb/package/qa.py
new file mode 100644
index 00000000000..93b458a101a
--- /dev/null
+++ b/openbb_sdk/openbb/package/qa.py
@@ -0,0 +1,375 @@
+### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
+
+from typing import List, Literal, Union
+
+import openbb_provider
+import openbb_qa.qa_models
+import pandas
+import pydantic
+import pydantic.types
+from openbb_core.app.model.obbject import OBBject
+from openbb_core.app.static.container import Container
+from openbb_core.app.static.filters import filter_inputs
+from pydantic import validate_arguments
+
+
+class CLASS_qa(Container):
+    """/qa
+    capm
+    kurtosis
+    normality
+    om
+    quantile
+    sh
+    skew
+    so
+    summary
+    unitroot
+    """
+
+    def __repr__(self) -> str:
+        return self.__doc__ or ""
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def capm(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+    ) -> OBBject[openbb_qa.qa_models.CAPMModel]:
+        """Capital Asset Pricing Model."""  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+        )
+
+        return self._command_runner.run(
+            "/qa/capm",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def kurtosis(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        window: pydantic.types.PositiveInt,
+    ) -> OBBject[List]:
+        """Kurtosis.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+        window : PositiveInt
+            Window size.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            Kurtosis.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            window=window,
+        )
+
+        return self._command_runner.run(
+            "/qa/kurtosis",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def normality(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+    ) -> OBBject[openbb_qa.qa_models.NormalityModel]:
+        """
+        Normality Statistics.
+
+        - **Kurtosis**: whether the kurtosis of a sample differs from the normal distribution.
+        - **Skewness**: whether the skewness of a sample differs from the normal distribution.
+        - **Jarque-Bera**: whether the sample data has the skewness and kurtosis matching a normal distribution.
+        - **Shapiro-Wilk**: whether a random sample comes from a normal distribution.
+        - **Kolmogorov-Smirnov**: whether two underlying one-dimensional probability distributions differ.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+
+        Returns
+        -------
+        OBBject[NormalityModel]
+            Normality tests summary. See qa_models.NormalityModel for details.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+        )
+
+        return self._command_runner.run(
+            "/qa/normality",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def om(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        threshold_start: float = 0.0,
+        threshold_end: float = 1.5,
+    ) -> OBBject[List]:
+        """Omega Ratio.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+        threshold_start : float, optional
+            Start threshold, by default 0.0
+        threshold_end : float, optional
+            End threshold, by default 1.5
+
+        Returns
+        -------
+        OBBject[List[OmegaModel]]
+            Omega ratios.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            threshold_start=threshold_start,
+            threshold_end=threshold_end,
+        )
+
+        return self._command_runner.run(
+            "/qa/om",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def quantile(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        window: pydantic.types.PositiveInt,
+        quantile_pct: pydantic.types.NonNegativeFloat = 0.5,
+    ) -> OBBject[List]:
+        """Quantile."""  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            window=window,
+            quantile_pct=quantile_pct,
+        )
+
+        return self._command_runner.run(
+            "/qa/quantile",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def sh(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        rfr: float = 0.0,
+        window: pydantic.types.PositiveInt = 252,
+    ) -> OBBject[List]:
+        """Sharpe Ratio.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+        rfr : float, optional
+            Risk-free rate, by default 0.0
+        window : PositiveInt, optional
+            Window size, by default 252
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            Sharpe ratio.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            rfr=rfr,
+            window=window,
+        )
+
+        return self._command_runner.run(
+            "/qa/sh",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def skew(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        window: pydantic.types.PositiveInt,
+    ) -> OBBject[List]:
+        """Skewness.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+        window : PositiveInt
+            Window size.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            Skewness.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            window=window,
+        )
+
+        return self._command_runner.run(
+            "/qa/skew",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def so(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        target_return: float = 0.0,
+        window: pydantic.types.PositiveInt = 252,
+        adjusted: bool = False,
+    ) -> OBBject[List]:
+        """Sortino Ratio.
+
+        For method & terminology see: http://www.redrockcapital.com/Sortino__A__Sharper__Ratio_Red_Rock_Capital.pdf
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+        target_return : float, optional
+            Target return, by default 0.0
+        window : PositiveInt, optional
+            Window size, by default 252
+        adjusted : bool, optional
+            Adjust sortino ratio to compare it to sharpe ratio, by default False
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            Sortino ratio.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            target_return=target_return,
+            window=window,
+            adjusted=adjusted,
+        )
+
+        return self._command_runner.run(
+            "/qa/so",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def summary(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+    ) -> OBBject[openbb_qa.qa_models.SummaryModel]:
+        """Summary.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+
+        Returns
+        -------
+        OBBject[SummaryModel]
+            Summary table.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+        )
+
+        return self._command_runner.run(
+            "/qa/summary",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def unitroot(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str,
+        fuller_reg: Literal["c", "ct", "ctt", "nc"] = "c",
+        kpss_reg: Literal["c", "ct"] = "c",
+    ) -> OBBject[openbb_qa.qa_models.UnitRootModel]:
+        """Unit Root Test.
+
+        Augmented Dickey-Fuller test for unit root.
+        Kwiatkowski-Phillips-Schmidt-Shin test for unit root.
+
+        Parameters
+        ----------
+        data : List[Data]
+            Time series data.
+        target : str
+            Target column name.
+        fuller_reg : Literal["c", "ct", "ctt", "nc", "c"]
+            Regression type for ADF test.
+        kpss_reg : Literal["c", "ct"]
+            Regression type for KPSS test.
+
+        Returns
+        -------
+        OBBject[UnitRootModel]
+            Unit root tests summary.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            fuller_reg=fuller_reg,
+            kpss_reg=kpss_reg,
+        )
+
+        return self._command_runner.run(
+            "/qa/unitroot",
+            **inputs,
+        )
diff --git a/openbb_sdk/openbb/package/stocks.py b/openbb_sdk/openbb/package/stocks.py
index 1a66cfe92da..a96fdf114c4 100644
--- a/openbb_sdk/openbb/package/stocks.py
+++ b/openbb_sdk/openbb/package/stocks.py
@@ -1,15 +1,16 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
 import datetime
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
 import pydantic
-import typing_extensions
+import pydantic.main
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
-from pydantic import validate_arguments
+from pydantic import BaseModel, validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_stocks(Container):
@@ -17,10 +18,13 @@ class CLASS_stocks(Container):
     /ca
     /dd
     /fa
+    info
     load
     multiples
     news
+    /options
     quote
+    search
     """
 
     def __repr__(self) -> str:
@@ -45,26 +49,143 @@ class CLASS_stocks(Container):
         return stocks_fa.CLASS_stocks_fa(command_runner=self._command_runner)
 
     @validate_arguments
-    def load(
+    def info(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        start_date: typing_extensions.Annotated[
+        provider: Optional[Literal["cboe"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Get general price and performance metrics of a stock.
+
+        Parameters
+        ----------
+        symbol : Union[str, List[str]]
+            Symbol to get data for.
+        provider : Optional[Literal['cboe']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'cboe' if there is
+            no default.
+
+        Returns
+        -------
+        OBBject
+            results : List[StockInfo]
+                Serializable results.
+            provider : Optional[Literal['cboe']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        StockInfo
+        ---------
+        symbol : Optional[str]
+            Symbol to get data for.
+        name : Optional[str]
+            Name associated with the ticker symbol.
+        price : Optional[float]
+            Last transaction price.
+        open : Optional[float]
+            Opening price of the stock.
+        high : Optional[float]
+            High price of the current trading day.
+        low : Optional[float]
+            Low price of the current trading day.
+        close : Optional[float]
+            Closing price of the most recent trading day.
+        change : Optional[float]
+            Change in price over the current trading period.
+        change_percent : Optional[float]
+            Percent change in price over the current trading period.
+        prev_close : Optional[float]
+            Previous closing price.
+        type : Optional[str]
+            Type of asset. (provider: cboe)
+        exchange_id : Optional[int]
+            The Exchange ID number. (provider: cboe)
+        tick : Optional[str]
+            Whether the last sale was an up or down tick. (provider: cboe)
+        bid : Optional[float]
+            Current bid price. (provider: cboe)
+        bid_size : Optional[float]
+            Bid lot size. (provider: cboe)
+        ask : Optional[float]
+            Current ask price. (provider: cboe)
+        ask_size : Optional[float]
+            Ask lot size. (provider: cboe)
+        volume : Optional[float]
+            Stock volume for the current trading day. (provider: cboe)
+        iv30 : Optional[float]
+            The 30-day implied volatility of the stock. (provider: cboe)
+        iv30_change : Optional[float]
+            Change in 30-day implied volatility of the stock. (provider: cboe)
+        last_trade_timestamp : Optional[datetime]
+            Last trade timestamp for the stock. (provider: cboe)
+        iv30_annual_high : Optional[float]
+            The 1-year high of implied volatility. (provider: cboe)
+        hv30_annual_high : Optional[float]
+            The 1-year high of realized volatility. (provider: cboe)
+        iv30_annual_low : Optional[float]
+            The 1-year low of implied volatility. (provider: cboe)
+        hv30_annual_low : Optional[float]
+            The 1-year low of realized volatility. (provider: cboe)
+        iv60_annual_high : Optional[float]
+            The 60-day high of implied volatility. (provider: cboe)
+        hv60_annual_high : Optional[float]
+            The 60-day high of realized volatility. (provider: cboe)
+        iv60_annual_low : Optional[float]
+            The 60-day low of implied volatility. (provider: cboe)
+        hv60_annual_low : Optional[float]
+            The 60-day low of realized volatility. (provider: cboe)
+        iv90_annual_high : Optional[float]
+            The 90-day high of implied volatility. (provider: cboe)
+        hv90_annual_high : Optional[float]
+            The 90-day high of realized volatility. (provider: cboe)"""  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/stocks/info",
+            **inputs,
+        )
+
+    @validate_arguments
+    def load(
+        self,
+        symbol: Annotated[
+            Union[str, List[str]],
+            OpenBBCustomParameter(description="Symbol to get data for."),
+        ],
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
         chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[
+            Literal["alpha_vantage", "cboe", "fmp", "intrinio", "polygon", "yfinance"]
+        ] = None,
         **kwargs
     ) -> OBBject[List]:
         """Load stock data for a specific ticker.
@@ -79,31 +200,59 @@ class CLASS_stocks(Container):
             End date of the data, in YYYY-MM-DD format.
         chart : bool
             Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['alpha_vantage', 'cboe', 'fmp', 'intrinio', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
-            If None, the provider specified in defaults is selected or 'fmp' if there is
+            If None, the provider specified in defaults is selected or 'alpha_vantage' if there is
             no default.
-        timeseries : Union[pydantic.types.NonNegativeInt, NoneType]
+        period : Union[Literal['intraday', 'daily', 'weekly', 'monthly'], Literal['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max'], NoneType]
+            None
+        interval : Union[Literal['1min', '5min', '15min', '30min', '60min'], NoneType, Literal['1d', '1m'], Literal['1min', '5min', '15min', '30min', '1hour', '4hour', '1day'], Literal['1m', '2m', '5m', '15m', '30m', '60m', '90m', '1h', '1d', '5d', '1wk', '1mo', '3mo']]
+            None
+        adjusted : Optional[bool]
+            None
+        extended_hours : Optional[bool]
+            Extended trading hours during pre-market and after-hours. (provider: alpha_vantage)
+        month : Optional[str]
+            Query a specific month in history (in YYYY-MM format). (provider: alpha_vantage)
+        outputsize : Optional[Literal['compact', 'full']]
+            Compact returns only the latest 100 data points in the intraday time series; full returns trailing 30 days of the most recent intraday data if the month parameter (see above) is not specified, or the full intraday data for a specific month in history if the month parameter is specified. (provider: alpha_vantage)
+        timeseries : Optional[pydantic.types.NonNegativeInt]
             Number of days to look back. (provider: fmp)
-        interval : Literal['1min', '5min', '15min', '30min', '1hour', '4hour', '1day']
-            Interval of the data to fetch. (provider: fmp)
+        timezone : Optional[Literal['Africa/Algiers', 'Africa/Cairo', 'Africa/Casablanca', 'Africa/Harare', 'Africa/Johannesburg', 'Africa/Monrovia', 'Africa/Nairobi', 'America/Argentina/Buenos_Aires', 'America/Bogota', 'America/Caracas', 'America/Chicago', 'America/Chihuahua', 'America/Denver', 'America/Godthab', 'America/Guatemala', 'America/Guyana', 'America/Halifax', 'America/Indiana/Indianapolis', 'America/Juneau', 'America/La_Paz', 'America/Lima', 'America/Los_Angeles', 'America/Mazatlan', 'America/Mexico_City', 'America/Monterrey', 'America/Montevideo', 'America/New_York', 'America/Phoenix', 'America/Regina', 'America/Santiago', 'America/Sao_Paulo', 'America/St_Johns', 'America/Tijuana', 'Asia/Almaty', 'Asia/Baghdad', 'Asia/Baku', 'Asia/Bangkok', 'Asia/Chongqing', 'Asia/Colombo', 'Asia/Dhaka', 'Asia/Hong_Kong', 'Asia/Irkutsk', 'Asia/Jakarta', 'Asia/Jerusalem', 'Asia/Kabul', 'Asia/Kamchatka', 'Asia/Karachi', 'Asia/Kathmandu', 'Asia/Kolkata', 'Asia/Krasnoyarsk', 'Asia/Kuala_Lumpur', 'Asia/Kuwait', 'Asia/Magadan', 'Asia/Muscat', 'Asia/Novosibirsk', 'Asia/Rangoon', 'Asia/Riyadh', 'Asia/Seoul', 'Asia/Shanghai', 'Asia/Singapore', 'Asia/Srednekolymsk', 'Asia/Taipei', 'Asia/Tashkent', 'Asia/Tbilisi', 'Asia/Tehran', 'Asia/Tokyo', 'Asia/Ulaanbaatar', 'Asia/Urumqi', 'Asia/Vladivostok', 'Asia/Yakutsk', 'Asia/Yekaterinburg', 'Asia/Yerevan', 'Atlantic/Azores', 'Atlantic/Cape_Verde', 'Atlantic/South_Georgia', 'Australia/Adelaide', 'Australia/Brisbane', 'Australia/Darwin', 'Australia/Hobart', 'Australia/Melbourne', 'Australia/Perth', 'Australia/Sydney', 'Etc/UTC', 'UTC', 'Europe/Amsterdam', 'Europe/Athens', 'Europe/Belgrade', 'Europe/Berlin', 'Europe/Bratislava', 'Europe/Brussels', 'Europe/Bucharest', 'Europe/Budapest', 'Europe/Copenhagen', 'Europe/Dublin', 'Europe/Helsinki', 'Europe/Istanbul', 'Europe/Kaliningrad', 'Europe/Kiev', 'Europe/Lisbon', 'Europe/Ljubljana', 'Europe/London', 'Europe/Madrid', 'Europe/Minsk', 'Europe/Moscow', 'Europe/Paris', 'Europe/Prague', 'Europe/Riga', 'Europe/Rome', 'Europe/Samara', 'Europe/Sarajevo', 'Europe/Skopje', 'Europe/Sofia', 'Europe/Stockholm', 'Europe/Tallinn', 'Europe/Vienna', 'Europe/Vilnius', 'Europe/Volgograd', 'Europe/Warsaw', 'Europe/Zagreb', 'Pacific/Apia', 'Pacific/Auckland', 'Pacific/Chatham', 'Pacific/Fakaofo', 'Pacific/Fiji', 'Pacific/Guadalcanal', 'Pacific/Guam', 'Pacific/Honolulu', 'Pacific/Majuro', 'Pacific/Midway', 'Pacific/Noumea', 'Pacific/Pago_Pago', 'Pacific/Port_Moresby', 'Pacific/Tongatapu']]
+            Returns trading times in this timezone. (provider: intrinio)
+        source : Optional[Literal['realtime', 'delayed', 'nasdaq_basic']]
+            The source of the data. (provider: intrinio)
+        start_time : Optional[datetime.time]
+            Return intervals starting at the specified time on the `start_date` formatted as 'hh:mm:ss'. (provider: intrinio)
+        end_time : Optional[datetime.time]
+            Return intervals stopping at the specified time on the `end_date` formatted as 'hh:mm:ss'. (provider: intrinio)
+        interval_size : Optional[Literal['1m', '5m', '10m', '15m', '30m', '60m', '1h']]
+            The data time frequency. (provider: intrinio)
+        limit : Union[pydantic.types.NonNegativeInt, NoneType, pydantic.types.PositiveInt]
+            None
+        next_page : Optional[str]
+            Token to get the next page of data from a previous API call. (provider: intrinio)
+        all_pages : Optional[bool]
+            Returns all pages of data from the API call at once. (provider: intrinio)
         timespan : Literal['minute', 'hour', 'day', 'week', 'month', 'quarter', 'year']
             Timespan of the data. (provider: polygon)
         sort : Literal['asc', 'desc']
             Sort order of the data. (provider: polygon)
-        limit : PositiveInt
-            The number of data entries to return. (provider: polygon)
-        adjusted : bool
-            Whether the data is adjusted. (provider: polygon)
         multiplier : PositiveInt
             Multiplier of the timespan. (provider: polygon)
+        prepost : bool
+            Include Pre and Post market data. (provider: yfinance)
+        adjust : bool
+            Adjust all the data automatically. (provider: yfinance)
+        back_adjust : bool
+            Back-adjusted data to mimic true historical prices. (provider: yfinance)
 
         Returns
         -------
         OBBject
-            results : List[StockEOD]
+            results : List[StockHistorical]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['alpha_vantage', 'cboe', 'fmp', 'intrinio', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -112,8 +261,8 @@ class CLASS_stocks(Container):
             metadata: Optional[Metadata]
                 Metadata info about the command execution.
 
-        StockEOD
-        --------
+        StockHistorical
+        ---------------
         date : Optional[datetime]
             The date of the data.
         open : Optional[PositiveFloat]
@@ -124,10 +273,22 @@ class CLASS_stocks(Container):
             The low price of the symbol.
         close : Optional[PositiveFloat]
             The close price of the symbol.
-        volume : Optional[float]
+        volume : Optional[NonNegativeInt]
             The volume of the symbol.
         vwap : Optional[PositiveFloat]
             Volume Weighted Average Price of the symbol.
+        adjusted_close : Optional[PositiveFloat]
+            The adjusted close price of the symbol. (provider: alpha_vantage)
+        dividend_amount : Optional[NonNegativeFloat]
+            Dividend amount paid for the corresponding date. (provider: alpha_vantage)
+        split_coefficient : Optional[NonNegativeFloat]
+            Split coefficient for the corresponding date. (provider: alpha_vantage)
+        calls_volume : Optional[float]
+            Number of calls traded during the most recent trading period. Only valid if interval is 1m. (provider: cboe)
+        puts_volume : Optional[float]
+            Number of puts traded during the most recent trading period. Only valid if interval is 1m. (provider: cboe)
+        total_options_volume : Optional[float]
+            Total number of options traded during the most recent trading period. Only valid if interval is 1m. (provider: cboe)
         adj_close : Optional[float]
             Adjusted Close Price of the symbol. (provider: fmp)
         unadjusted_volume : Optional[float]
@@ -140,7 +301,13 @@ class CLASS_stocks(Container):
             Human readable format of the date. (provider: fmp)
         change_over_time : Optional[float]
             Change \\% in the price of the symbol over a period of time. (provider: fmp)
-        n : Optional[PositiveInt]
+        close_time : Optional[datetime]
+            The timestamp that represents the end of the interval span. (provider: intrinio)
+        interval : Optional[str]
+            The data time frequency. (provider: intrinio)
+        average : Optional[float]
+            Average trade price of an individual stock during the interval. (provider: intrinio)
+        transactions : Optional[PositiveInt]
             Number of transactions for the symbol in the time period. (provider: polygon)
         """  # noqa: E501
 
@@ -165,16 +332,16 @@ class CLASS_stocks(Container):
     @validate_arguments
     def multiples(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        limit: typing_extensions.Annotated[
-            Union[int, None],
+        limit: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 100,
         chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Get valuation multiples for a stock ticker.
@@ -183,11 +350,11 @@ class CLASS_stocks(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        limit : Union[int, NoneType]
+        limit : Optional[int]
             The number of data entries to return.
         chart : bool
             Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -197,7 +364,7 @@ class CLASS_stocks(Container):
         OBBject
             results : List[StockMultiples]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -349,23 +516,25 @@ class CLASS_stocks(Container):
     @validate_arguments
     def news(
         self,
-        symbols: typing_extensions.Annotated[
+        symbols: Annotated[
             str, OpenBBCustomParameter(description="Symbol to get data for.")
         ],
-        page: typing_extensions.Annotated[
+        page: Annotated[
             int,
             OpenBBCustomParameter(
                 description="Page of the stock news to be retrieved."
             ),
         ] = 0,
-        limit: typing_extensions.Annotated[
-            Union[pydantic.types.NonNegativeInt, None],
+        limit: Annotated[
+            Optional[pydantic.types.NonNegativeInt],
             OpenBBCustomParameter(description="Number of results to return per page."),
         ] = 15,
         chart: bool = False,
-        provider: Union[Literal["benzinga", "fmp", "polygon"], None] = None,
+        provider: Optional[
+            Literal["benzinga", "fmp", "intrinio", "polygon", "yfinance"]
+        ] = None,
         **kwargs
-    ) -> OBBject[List]:
+    ) -> OBBject[BaseModel]:
         """Get news for one or more stock tickers.
 
         Parameters
@@ -374,59 +543,63 @@ class CLASS_stocks(Container):
             Symbol to get data for.
         page : int
             Page of the stock news to be retrieved.
-        limit : Union[pydantic.types.NonNegativeInt, NoneType]
+        limit : Optional[pydantic.types.NonNegativeInt]
             Number of results to return per page.
         chart : bool
             Whether to create a chart or not, by default False.
-        provider : Union[Literal['benzinga', 'fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['benzinga', 'fmp', 'intrinio', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'benzinga' if there is
             no default.
         display_output : Literal['headline', 'summary', 'full', 'all']
             Type of data to return. (provider: benzinga)
-        date : Union[datetime.datetime, NoneType]
+        date : Optional[datetime.datetime]
             Date of the news to retrieve. (provider: benzinga)
-        date_from : Union[datetime.datetime, NoneType]
+        date_from : Optional[datetime.datetime]
             Start date of the news to retrieve. (provider: benzinga)
-        date_to : Union[datetime.datetime, NoneType]
+        date_to : Optional[datetime.datetime]
             End date of the news to retrieve. (provider: benzinga)
-        updated_since : Union[int, NoneType]
+        updated_since : Optional[int]
             Number of seconds since the news was updated. (provider: benzinga)
-        published_since : Union[int, NoneType]
+        published_since : Optional[int]
             Number of seconds since the news was published. (provider: benzinga)
         sort : Union[Literal['published_at', 'updated_at', 'title', 'author', 'channel', 'ticker', 'topic', 'content_type'], NoneType, str]
             None
-        isin : Union[str, NoneType]
+        isin : Optional[str]
             The ISIN of the news to retrieve. (provider: benzinga)
-        cusip : Union[str, NoneType]
+        cusip : Optional[str]
             The CUSIP of the news to retrieve. (provider: benzinga)
-        channels : Union[str, NoneType]
+        channels : Optional[str]
             Channels of the news to retrieve. (provider: benzinga)
-        topics : Union[str, NoneType]
+        topics : Optional[str]
             Topics of the news to retrieve. (provider: benzinga)
-        authors : Union[str, NoneType]
+        authors : Optional[str]
             Authors of the news to retrieve. (provider: benzinga)
-        content_types : Union[str, NoneType]
+        content_types : Optional[str]
             Content types of the news to retrieve. (provider: benzinga)
-        ticker_lt : Union[str, NoneType]
+        next_page : Optional[str]
+            Token to get the next page of data from a previous API call. (provider: intrinio)
+        all_pages : Optional[bool]
+            Returns all pages of data from the API call at once. (provider: intrinio)
+        ticker_lt : Optional[str]
             Less than, by default None (provider: polygon)
-        ticker_lte : Union[str, NoneType]
+        ticker_lte : Optional[str]
             Less than or equal, by default None (provider: polygon)
-        ticker_gt : Union[str, NoneType]
+        ticker_gt : Optional[str]
             Greater than, by default None (provider: polygon)
-        ticker_gte : Union[str, NoneType]
+        ticker_gte : Optional[str]
             Greater than or equal, by default None (provider: polygon)
-        published_utc : Union[str, NoneType]
+        published_utc : Optional[str]
             Published date of the query, by default None (provider: polygon)
-        published_utc_lt : Union[str, NoneType]
+        published_utc_lt : Optional[str]
             Less than, by default None (provider: polygon)
-        published_utc_lte : Union[str, NoneType]
+        published_utc_lte : Optional[str]
             Less than or equal, by default None (provider: polygon)
-        published_utc_gt : Union[str, NoneType]
+        published_utc_gt : Optional[str]
             Greater than, by default None (provider: polygon)
-        published_utc_gte : Union[str, NoneType]
+        published_utc_gte : Optional[str]
             Greater than or equal, by default None (provider: polygon)
-        order : Union[Literal['asc', 'desc'], NoneType]
+        order : Optional[Literal['asc', 'desc']]
             Sort order of the query, by default None (provider: polygon)
 
         Returns
@@ -434,7 +607,7 @@ class CLASS_stocks(Container):
         OBBject
             results : List[StockNews]
                 Serializable results.
-            provider : Union[Literal['benzinga', 'fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['benzinga', 'fmp', 'intrinio', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -469,20 +642,28 @@ class CLASS_stocks(Container):
             URL to the image of the news source. (provider: fmp)
         site : Optional[str]
             Name of the news source. (provider: fmp)
+        id : Optional[str]
+            Intrinio ID for the news article. (provider: intrinio)
         amp_url : Optional[str]
             AMP URL. (provider: polygon)
         author : Optional[str]
             Author of the article. (provider: polygon)
-        id : Optional[str]
-            Article ID. (provider: polygon)
         image_url : Optional[str]
             Image URL. (provider: polygon)
         keywords : Optional[List[str]]
             Keywords in the article (provider: polygon)
-        publisher : Optional[PolygonPublisher]
+        publisher : Union[PolygonPublisher, NoneType, str]
             Publisher of the article. (provider: polygon)
         tickers : Optional[List[str]]
-            Tickers covered in the article. (provider: polygon)"""  # noqa: E501
+            Tickers covered in the article. (provider: polygon)
+        uuid : Optional[str]
+            Unique identifier for the news article (provider: yfinance)
+        type : Optional[str]
+            Type of the news article (provider: yfinance)
+        thumbnail : Optional[Mapping[str, Any]]
+            Thumbnail related data to the ticker news article. (provider: yfinance)
+        related_tickers : Optional[str]
+            Tickers related to the news article. (provider: yfinance)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -502,15 +683,20 @@ class CLASS_stocks(Container):
             **inputs,
         )
 
+    @property
+    def options(self):  # route = "/stocks/options"
+        from . import stocks_options
+
+        return stocks_options.CLASS_stocks_options(command_runner=self._command_runner)
+
     @validate_arguments
     def quote(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp", "intrinio"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Load stock data for a specific ticker.
@@ -519,19 +705,19 @@ class CLASS_stocks(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp', 'intrinio']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
+        source : Literal['iex', 'bats', 'bats_delayed', 'utp_delayed', 'cta_a_delayed', 'cta_b_delayed', 'intrinio_mx', 'intrinio_mx_plus', 'delayed_sip']
+            Source of the data. (provider: intrinio)
 
         Returns
         -------
         OBBject
             results : List[StockQuote]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp', 'intrinio']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -542,50 +728,90 @@ class CLASS_stocks(Container):
 
         StockQuote
         ----------
-        symbol : Optional[str]
-            Symbol of the company.
-        name : Optional[str]
-            Name of the company.
-        price : Optional[float]
-            Current trading price of the stock.
-        changes_percentage : Optional[float]
-            Change percentage of the stock price.
-        change : Optional[float]
-            Change of the stock price.
         day_low : Optional[float]
             Lowest price of the stock in the current trading day.
         day_high : Optional[float]
             Highest price of the stock in the current trading day.
-        year_high : Optional[float]
-            Highest price of the stock in the last 52 weeks.
-        year_low : Optional[float]
-            Lowest price of the stock in the last 52 weeks.
-        market_cap : Optional[float]
-            Market cap of the company.
-        price_avg50 : Optional[float]
-            50 days average price of the stock.
-        price_avg200 : Optional[float]
-            200 days average price of the stock.
-        volume : Optional[int]
-            Volume of the stock in the current trading day.
-        avg_volume : Optional[int]
-            Average volume of the stock in the last 10 trading days.
-        exchange : Optional[str]
-            Exchange the stock is traded on.
-        open : Optional[float]
-            Opening price of the stock in the current trading day.
-        previous_close : Optional[float]
-            Previous closing price of the stock.
-        eps : Optional[float]
-            Earnings per share of the stock.
-        pe : Optional[float]
-            Price earnings ratio of the stock.
-        earnings_announcement : Optional[str]
-            Earnings announcement date of the stock.
-        shares_outstanding : Optional[int]
-            Number of shares outstanding of the stock.
         date : Optional[datetime]
-            Timestamp of the stock quote."""  # noqa: E501
+            Timestamp of the stock quote.
+        symbol : Optional[str]
+            Symbol of the company. (provider: fmp)
+        name : Optional[str]
+            Name of the company. (provider: fmp)
+        price : Optional[float]
+            Current trading price of the stock. (provider: fmp)
+        changes_percentage : Optional[float]
+            Change percentage of the stock price. (provider: fmp)
+        change : Optional[float]
+            Change in the stock price. (provider: fmp)
+        year_high : Optional[float]
+            Highest price of the stock in the last 52 weeks. (provider: fmp)
+        year_low : Optional[float]
+            Lowest price of the stock in the last 52 weeks. (provider: fmp)
+        market_cap : Optional[float]
+            Market cap of the company. (provider: fmp)
+        price_avg50 : Optional[float]
+            50 days average price of the stock. (provider: fmp)
+        price_avg200 : Optional[float]
+            200 days average price of the stock. (provider: fmp)
+        volume : Optional[int]
+            Volume of the stock in the current trading day. (provider: fmp)
+        avg_volume : Optional[int]
+            Average volume of the stock in the last 10 trading days. (provider: fmp)
+        exchange : Optional[str]
+            Exchange the stock is traded on. (provider: fmp)
+        open : Optional[float]
+            Opening price of the stock in the current trading day. (provider: fmp)
+        previous_close : Optional[float]
+            Previous closing price of the stock. (provider: fmp)
+        eps : Optional[float]
+            Earnings per share of the stock. (provider: fmp)
+        pe : Optional[float]
+            Price earnings ratio of the stock. (provider: fmp)
+        earnings_announcement : Optional[str]
+            Earnings announcement date of the stock. (provider: fmp)
+        shares_outstanding : Optional[int]
+            Number of shares outstanding of the stock. (provider: fmp)
+        last_price : Optional[float]
+            Price of the last trade. (provider: intrinio)
+        last_time : Optional[datetime]
+            Date and Time when the last trade occurred. (provider: intrinio)
+        last_size : Optional[int]
+            Size of the last trade. (provider: intrinio)
+        bid_price : Optional[float]
+            Price of the top bid order. (provider: intrinio)
+        bid_size : Optional[int]
+            Size of the top bid order. (provider: intrinio)
+        ask_price : Optional[float]
+            Price of the top ask order. (provider: intrinio)
+        ask_size : Optional[int]
+            Size of the top ask order. (provider: intrinio)
+        open_price : Optional[float]
+            Open price for the trading day. (provider: intrinio)
+        close_price : Optional[float]
+            Closing price for the trading day (IEX source only). (provider: intrinio)
+        high_price : Optional[float]
+            High Price for the trading day. (provider: intrinio)
+        low_price : Optional[float]
+            Low Price for the trading day. (provider: intrinio)
+        exchange_volume : Optional[int]
+            Number of shares exchanged during the trading day on the exchange. (provider: intrinio)
+        market_volume : Optional[int]
+            Number of shares exchanged during the trading day for the whole market. (provider: intrinio)
+        updated_on : Optional[datetime]
+            Date and Time when the data was last updated. (provider: intrinio)
+        source : Optional[str]
+            Source of the data. (provider: intrinio)
+        listing_venue : Optional[str]
+            Listing venue where the trade took place (SIP source only). (provider: intrinio)
+        sales_conditions : Optional[str]
+            Indicates any sales condition modifiers associated with the trade. (provider: intrinio)
+        quote_conditions : Optional[str]
+            Indicates any quote condition modifiers associated with the trade. (provider: intrinio)
+        market_center_code : Optional[str]
+            Market center character code. (provider: intrinio)
+        is_darkpool : Optional[bool]
+            Whether or not the current trade is from a darkpool. (provider: intrinio)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -595,10 +821,74 @@ class CLASS_stocks(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
             "/stocks/quote",
             **inputs,
         )
+
+    @validate_arguments
+    def search(
+        self,
+        query: Annotated[str, OpenBBCustomParameter(description="Search query.")] = "",
+        ticker: Annotated[
+            bool,
+            OpenBBCustomParameter(description="Whether to search by ticker symbol."),
+        ] = False,
+        provider: Optional[Literal["cboe"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Search for a company or stock ticker.
+
+        Parameters
+        ----------
+        query : str
+            Search query.
+        ticker : bool
+            Whether to search by ticker symbol.
+        provider : Optional[Literal['cboe']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'cboe' if there is
+            no default.
+
+        Returns
+        -------
+        OBBject
+            results : List[StockSearch]
+                Serializable results.
+            provider : Optional[Literal['cboe']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        StockSearch
+        -----------
+        symbol : Optional[str]
+            Symbol to get data for.
+        name : Optional[str]
+            Name of the company.
+        dpm_name : Optional[str]
+            Name of the primary market maker. (provider: cboe)
+        post_station : Optional[str]
+            Post and station location on the CBOE trading floor. (provider: cboe)"""  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "query": query,
+                "ticker": ticker,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/stocks/search",
+            **inputs,
+        )
diff --git a/openbb_sdk/openbb/package/stocks_ca.py b/openbb_sdk/openbb/package/stocks_ca.py
index 173a3f97855..8c8d05c9d06 100644
--- a/openbb_sdk/openbb/package/stocks_ca.py
+++ b/openbb_sdk/openbb/package/stocks_ca.py
@@ -1,13 +1,13 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import BaseModel, validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_stocks_ca(Container):
@@ -21,12 +21,11 @@ class CLASS_stocks_ca(Container):
     @validate_arguments
     def peers(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[BaseModel]:
         """Company peers.
@@ -35,9 +34,7 @@ class CLASS_stocks_ca(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -47,7 +44,7 @@ class CLASS_stocks_ca(Container):
         OBBject
             results : List[StockPeers]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -71,7 +68,6 @@ class CLASS_stocks_ca(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/stocks_dd.py b/openbb_sdk/openbb/package/stocks_dd.py
index 990701d7fe5..2656ec811bf 100644
--- a/openbb_sdk/openbb/package/stocks_dd.py
+++ b/openbb_sdk/openbb/package/stocks_dd.py
@@ -1,13 +1,13 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_stocks_dd(Container):
@@ -21,11 +21,11 @@ class CLASS_stocks_dd(Container):
     @validate_arguments
     def sec(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        type: typing_extensions.Annotated[
+        type: Annotated[
             Literal[
                 "1",
                 "1-A",
@@ -130,16 +130,15 @@ class CLASS_stocks_dd(Container):
             ],
             OpenBBCustomParameter(description="Type of the SEC filing form."),
         ] = "10-K",
-        page: typing_extensions.Annotated[
-            Union[int, None],
+        page: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="Page number of the results."),
         ] = 0,
-        limit: typing_extensions.Annotated[
-            Union[int, None],
+        limit: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 100,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """SEC Filings.
@@ -150,13 +149,11 @@ class CLASS_stocks_dd(Container):
             Symbol to get data for.
         type : Literal['1', '1-A', '1-E', '1-K', '1-N', '1-SA', '1-U', '1-Z', '10', '10-D', '10-K', '10-M', '10-Q', '11-K', '12b-25', '13F', '13H', '144', '15', '15F', '17-H', '18', '18-K', '19b-4', '19b-4(e)', '19b-7', '2-E', '20-F', '24F-2', '25', '3', '4', '40-F', '5', '6-K', '7-M', '8-A', '8-K', '8-M', '9-M', 'ABS-15G', 'ABS-EE', 'ABS DD-15E', 'ADV', 'ADV-E', 'ADV-H', 'ADV-NR', 'ADV-W', 'ATS', 'ATS-N', 'ATS-R', 'BD', 'BD-N', 'BDW', 'C', 'CA-1', 'CB', 'CFPORTAL', 'CRS', 'CUSTODY', 'D', 'F-1', 'F-10', 'F-3', 'F-4', 'F-6', 'F-7', 'F-8', 'F-80', 'F-N', 'F-X', 'ID', 'MA', 'MA-I', 'MA-NR', 'MA-W', 'MSD', 'MSDW', 'N-14', 'N-17D-1', 'N-17f-1', 'N-17f-2', 'N-18f-1', 'N-1A', 'N-2', 'N-23c-3', 'N-27D-1', 'N-3', 'N-4', 'N-5', 'N-54A', 'N-54C', 'N-6', 'N-6EI-1', 'N-6F', 'N-8A', 'N-8B-2', 'N-8B-4', 'N-8F', 'N-CEN']
             Type of the SEC filing form.
-        page : Union[int, NoneType]
+        page : Optional[int]
             Page number of the results.
-        limit : Union[int, NoneType]
+        limit : Optional[int]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -166,7 +163,7 @@ class CLASS_stocks_dd(Container):
         OBBject
             results : List[SECFilings]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -203,7 +200,6 @@ class CLASS_stocks_dd(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/stocks_fa.py b/openbb_sdk/openbb/package/stocks_fa.py
index 8fcc9e59626..370773c2854 100644
--- a/openbb_sdk/openbb/package/stocks_fa.py
+++ b/openbb_sdk/openbb/package/stocks_fa.py
@@ -1,16 +1,16 @@
 ### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
 
 import datetime
-from typing import List, Literal, Union
+from typing import List, Literal, Optional, Union
 
 import pydantic
 import pydantic.main
-import typing_extensions
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.filters import filter_inputs
 from pydantic import BaseModel, validate_arguments
+from typing_extensions import Annotated
 
 
 class CLASS_stocks_fa(Container):
@@ -50,22 +50,21 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def balance(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
+        period: Annotated[
             Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        limit: typing_extensions.Annotated[
-            Union[pydantic.types.NonNegativeInt, None],
+        limit: Annotated[
+            Optional[pydantic.types.NonNegativeInt],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 12,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[Literal["fmp", "intrinio", "polygon", "yfinance"]] = None,
         **kwargs
-    ) -> OBBject[List]:
+    ) -> OBBject[BaseModel]:
         """Balance Sheet.
 
         Parameters
@@ -74,47 +73,47 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         period : Literal['annual', 'quarter']
             Period of the data to return.
-        limit : Union[pydantic.types.NonNegativeInt, NoneType]
+        limit : Optional[pydantic.types.NonNegativeInt]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['fmp', 'intrinio', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
-        cik : Union[str, NoneType]
-            None
-        company_name : Union[str, NoneType]
+        type : Literal['reported', 'standardized']
+            Type of the statement to be fetched. (provider: intrinio)
+        year : Optional[int]
+            Year of the statement to be fetched. (provider: intrinio)
+        company_name : Optional[str]
             Name of the company. (provider: polygon)
-        company_name_search : Union[str, NoneType]
+        company_name_search : Optional[str]
             Name of the company to search. (provider: polygon)
-        sic : Union[str, NoneType]
+        sic : Optional[str]
             The Standard Industrial Classification (SIC) of the company. (provider: polygon)
-        filing_date : Union[datetime.date, NoneType]
+        filing_date : Optional[datetime.date]
             Filing date of the financial statement. (provider: polygon)
-        filing_date_lt : Union[datetime.date, NoneType]
+        filing_date_lt : Optional[datetime.date]
             Filing date less than the given date. (provider: polygon)
-        filing_date_lte : Union[datetime.date, NoneType]
+        filing_date_lte : Optional[datetime.date]
             Filing date less than or equal to the given date. (provider: polygon)
-        filing_date_gt : Union[datetime.date, NoneType]
+        filing_date_gt : Optional[datetime.date]
             Filing date greater than the given date. (provider: polygon)
-        filing_date_gte : Union[datetime.date, NoneType]
+        filing_date_gte : Optional[datetime.date]
             Filing date greater than or equal to the given date. (provider: polygon)
-        period_of_report_date : Union[datetime.date, NoneType]
+        period_of_report_date : Optional[datetime.date]
             Period of report date of the financial statement. (provider: polygon)
-        period_of_report_date_lt : Union[datetime.date, NoneType]
+        period_of_report_date_lt : Optional[datetime.date]
             Period of report date less than the given date. (provider: polygon)
-        period_of_report_date_lte : Union[datetime.date, NoneType]
+        period_of_report_date_lte : Optional[datetime.date]
             Period of report date less than or equal to the given date. (provider: polygon)
-        period_of_report_date_gt : Union[datetime.date, NoneType]
+        period_of_report_date_gt : Optional[datetime.date]
             Period of report date greater than the given date. (provider: polygon)
-        period_of_report_date_gte : Union[datetime.date, NoneType]
+        period_of_report_date_gte : Optional[datetime.date]
             Period of report date greater than or equal to the given date. (provider: polygon)
-        include_sources : Union[bool, NoneType]
+        include_sources : Optional[bool]
             Whether to include the sources of the financial statement. (provider: polygon)
-        order : Union[Literal['asc', 'desc'], NoneType]
+        order : Optional[Literal['asc', 'desc']]
             Order of the financial statement. (provider: polygon)
-        sort : Union[Literal['filing_date', 'period_of_report_date'], NoneType]
+        sort : Optional[Literal['filing_date', 'period_of_report_date']]
             Sort of the financial statement. (provider: polygon)
 
         Returns
@@ -122,7 +121,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[BalanceSheet]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['fmp', 'intrinio', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -133,116 +132,114 @@ class CLASS_stocks_fa(Container):
 
         BalanceSheet
         ------------
+        symbol : Optional[str]
+            Symbol to get data for.
         date : Optional[date]
             Date of the fetched statement.
-        symbol : Optional[str]
-            Symbol of the company.
-        cik : Optional[int]
-            Central Index Key.
-        currency : Optional[str]
-            Reporting currency.
-        filing_date : Optional[date]
-            Filling date.
-        accepted_date : Optional[datetime]
-            Accepted date.
         period : Optional[str]
             Reporting period of the statement.
+        cik : Optional[int]
+            Central Index Key (CIK) of the company.
         cash_and_cash_equivalents : Optional[int]
             Cash and cash equivalents
         short_term_investments : Optional[int]
             Short-term investments
-        inventory : Optional[int]
-            Inventory
         net_receivables : Optional[int]
             Receivables, net
+        inventory : Optional[int]
+            Inventory
         other_current_assets : Optional[int]
             Other current assets
-        current_assets : Optional[int]
+        total_current_assets : Optional[int]
             Total current assets
-        long_term_investments : Optional[int]
-            Long-term investments
+        marketable_securities : Optional[int]
+            Marketable securities
         property_plant_equipment_net : Optional[int]
             Property, plant and equipment, net
         goodwill : Optional[int]
             Goodwill
         intangible_assets : Optional[int]
             Intangible assets
-        other_non_current_assets : Optional[int]
-            Other non-current assets
         tax_assets : Optional[int]
             Accrued income taxes
+        other_non_current_assets : Optional[int]
+            Other non-current assets
+        total_non_current_assets : Optional[int]
+            Total non-current assets
         other_assets : Optional[int]
             Other assets
-        noncurrent_assets : Optional[int]
-            None
-        assets : Optional[int]
-            None
+        total_assets : Optional[int]
+            Total assets
         account_payables : Optional[int]
-            None
-        other_current_liabilities : Optional[int]
-            None
+            Accounts payables
+        short_term_debt : Optional[int]
+            Short-term borrowings, Long-term debt due within one year, Operating lease obligations due within one year, Finance lease obligations due within one year
         tax_payables : Optional[int]
             Accrued income taxes
         deferred_revenue : Optional[int]
             Accrued income taxes, other deferred revenue
-        short_term_debt : Optional[int]
-            Short-term borrowings, Long-term debt due within one year, Operating lease obligations due within one year, Finance lease obligations due within one year
-        current_liabilities : Optional[int]
-            None
+        other_current_liabilities : Optional[int]
+            Other current liabilities
+        total_current_liabilities : Optional[int]
+            Total current liabilities
         long_term_debt : Optional[int]
             Long-term debt, Operating lease obligations, Long-term finance lease obligations
+        deferred_revenue_non_current : Optional[int]
+            Deferred revenue, non-current
+        deferred_tax_liabilities_non_current : Optional[int]
+            Deferred income taxes and other
         other_non_current_liabilities : Optional[int]
             Deferred income taxes and other
+        total_non_current_liabilities : Optional[int]
+            Total non-current liabilities
         other_liabilities : Optional[int]
-            None
-        noncurrent_liabilities : Optional[int]
-            None
-        liabilities : Optional[int]
-            None
-        common_stock : Optional[int]
-            None
-        other_stockholder_equity : Optional[int]
-            Capital in excess of par value
-        accumulated_other_comprehensive_income_loss : Optional[int]
-            Accumulated other comprehensive income (loss)
+            Other liabilities
+        total_liabilities : Optional[int]
+            Total liabilities
         preferred_stock : Optional[int]
             Preferred stock
+        common_stock : Optional[int]
+            Common stock
         retained_earnings : Optional[int]
             Retained earnings
+        accumulated_other_comprehensive_income_loss : Optional[int]
+            Accumulated other comprehensive income (loss)
+        other_shareholder_equity : Optional[int]
+            Other shareholder's equity
+        total_shareholder_equity : Optional[int]
+            Total shareholder's equity
+        total_equity : Optional[int]
+            Total equity
+        total_liabilities_and_shareholders_equity : Optional[int]
+            Total liabilities and shareholder's equity
         minority_interest : Optional[int]
             Minority interest
-        total_stockholders_equity : Optional[int]
-            None
-        total_equity : Optional[int]
-            None
-        total_liabilities_and_stockholders_equity : Optional[int]
-            None
         total_liabilities_and_total_equity : Optional[int]
-            None
+            Total liabilities and total equity
+        reported_currency : Optional[str]
+            Reported currency in the statement. (provider: fmp)
+        filling_date : Optional[date]
+            Filling date. (provider: fmp)
+        accepted_date : Optional[datetime]
+            Accepted date. (provider: fmp)
         calendar_year : Optional[int]
-            None
-        link : Optional[str]
-            None
-        final_link : Optional[str]
-            None
+            Calendar year. (provider: fmp)
         cash_and_short_term_investments : Optional[int]
-            None
+            Cash and short term investments (provider: fmp)
         goodwill_and_intangible_assets : Optional[int]
-            None
-        deferred_revenue_non_current : Optional[int]
-            None
-        total_investments : Optional[int]
-            None
+            Goodwill and Intangible Assets (provider: fmp)
         capital_lease_obligations : Optional[int]
-            None
-        deferred_tax_liabilities_non_current : Optional[int]
-            None
-        total_non_current_liabilities : Optional[int]
-            None
+            Capital lease obligations (provider: fmp)
+        total_investments : Optional[int]
+            Total investments (provider: fmp)
         total_debt : Optional[int]
-            None
+            Total debt (provider: fmp)
         net_debt : Optional[int]
-            None"""  # noqa: E501
+            Net debt (provider: fmp)
+        link : Optional[str]
+            Link to the statement. (provider: fmp)
+        final_link : Optional[str]
+            Link to the final statement. (provider: fmp)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -254,7 +251,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -265,16 +261,15 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def balance_growth(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        limit: typing_extensions.Annotated[
+        limit: Annotated[
             int,
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 10,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Balance Sheet Statement Growth.
@@ -285,9 +280,7 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         limit : int
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -297,7 +290,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[BalanceSheetGrowth]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -402,7 +395,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -413,20 +405,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def cal(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Show Dividend Calendar for a given start and end dates.
@@ -437,9 +428,7 @@ class CLASS_stocks_fa(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -449,7 +438,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[DividendCalendar]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -486,7 +475,6 @@ class CLASS_stocks_fa(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -497,22 +485,21 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def cash(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
+        period: Annotated[
             Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        limit: typing_extensions.Annotated[
-            Union[pydantic.types.NonNegativeInt, None],
+        limit: Annotated[
+            Optional[pydantic.types.NonNegativeInt],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 12,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[Literal["fmp", "intrinio", "polygon", "yfinance"]] = None,
         **kwargs
-    ) -> OBBject[List]:
+    ) -> OBBject[BaseModel]:
         """Cash Flow Statement.
 
         Parameters
@@ -521,47 +508,47 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         period : Literal['annual', 'quarter']
             Period of the data to return.
-        limit : Union[pydantic.types.NonNegativeInt, NoneType]
+        limit : Optional[pydantic.types.NonNegativeInt]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['fmp', 'intrinio', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
-        cik : Union[str, NoneType]
-            Central Index Key (CIK) of the company. (provider: fmp)
-        company_name : Union[str, NoneType]
+        type : Literal['reported', 'standardized']
+            Type of the statement to be fetched. (provider: intrinio)
+        year : Optional[int]
+            Year of the statement to be fetched. (provider: intrinio)
+        company_name : Optional[str]
             Name of the company. (provider: polygon)
-        company_name_search : Union[str, NoneType]
+        company_name_search : Optional[str]
             Name of the company to search. (provider: polygon)
-        sic : Union[str, NoneType]
+        sic : Optional[str]
             The Standard Industrial Classification (SIC) of the company. (provider: polygon)
-        filing_date : Union[datetime.date, NoneType]
+        filing_date : Optional[datetime.date]
             Filing date of the financial statement. (provider: polygon)
-        filing_date_lt : Union[datetime.date, NoneType]
+        filing_date_lt : Optional[datetime.date]
             Filing date less than the given date. (provider: polygon)
-        filing_date_lte : Union[datetime.date, NoneType]
+        filing_date_lte : Optional[datetime.date]
             Filing date less than or equal to the given date. (provider: polygon)
-        filing_date_gt : Union[datetime.date, NoneType]
+        filing_date_gt : Optional[datetime.date]
             Filing date greater than the given date. (provider: polygon)
-        filing_date_gte : Union[datetime.date, NoneType]
+        filing_date_gte : Optional[datetime.date]
             Filing date greater than or equal to the given date. (provider: polygon)
-        period_of_report_date : Union[datetime.date, NoneType]
+        period_of_report_date : Optional[datetime.date]
             Period of report date of the financial statement. (provider: polygon)
-        period_of_report_date_lt : Union[datetime.date, NoneType]
+        period_of_report_date_lt : Optional[datetime.date]
             Period of report date less than the given date. (provider: polygon)
-        period_of_report_date_lte : Union[datetime.date, NoneType]
+        period_of_report_date_lte : Optional[datetime.date]
             Period of report date less than or equal to the given date. (provider: polygon)
-        period_of_report_date_gt : Union[datetime.date, NoneType]
+        period_of_report_date_gt : Optional[datetime.date]
             Period of report date greater than the given date. (provider: polygon)
-        period_of_report_date_gte : Union[datetime.date, NoneType]
+        period_of_report_date_gte : Optional[datetime.date]
             Period of report date greater than or equal to the given date. (provider: polygon)
-        include_sources : Union[bool, NoneType]
+        include_sources : Optional[bool]
             Whether to include the sources of the financial statement. (provider: polygon)
-        order : Union[Literal['asc', 'desc'], NoneType]
+        order : Optional[Literal['asc', 'desc']]
             Order of the financial statement. (provider: polygon)
-        sort : Union[Literal['filing_date', 'period_of_report_date'], NoneType]
+        sort : Optional[Literal['filing_date', 'period_of_report_date']]
             Sort of the financial statement. (provider: polygon)
 
         Returns
@@ -569,7 +556,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[CashFlowStatement]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['fmp', 'intrinio', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -580,88 +567,100 @@ class CLASS_stocks_fa(Container):
 
         CashFlowStatement
         -----------------
+        symbol : Optional[str]
+            Symbol to get data for.
         date : Optional[date]
             Date of the fetched statement.
-        symbol : Optional[str]
-            Symbol of the company.
-        cik : Optional[int]
-            Central Index Key.
-        currency : Optional[str]
-            Reporting currency.
-        filing_date : Optional[date]
-            Filling date.
-        accepted_date : Optional[datetime]
-            Accepted date.
         period : Optional[str]
             Reporting period of the statement.
-        cash_at_beginning_of_period : Optional[int]
-            Cash at beginning of period.
+        cik : Optional[int]
+            Central Index Key (CIK) of the company.
         net_income : Optional[int]
             Net income.
         depreciation_and_amortization : Optional[int]
             Depreciation and amortization.
         stock_based_compensation : Optional[int]
             Stock based compensation.
-        other_non_cash_items : Optional[int]
-            Other non-cash items.
         deferred_income_tax : Optional[int]
             Deferred income tax.
-        inventory : Optional[int]
-            Inventory.
-        accounts_payables : Optional[int]
-            Accounts payables.
+        other_non_cash_items : Optional[int]
+            Other non-cash items.
+        changes_in_operating_assets_and_liabilities : Optional[int]
+            Changes in operating assets and liabilities.
         accounts_receivables : Optional[int]
             Accounts receivables.
-        change_in_working_capital : Optional[int]
-            Change in working capital.
-        other_working_capital : Optional[int]
-            Accrued expenses and other, Unearned revenue.
-        capital_expenditure : Optional[int]
-            Purchases of property and equipment.
-        other_investing_activities : Optional[int]
-            Proceeds from property and equipment sales and incentives.
-        acquisitions_net : Optional[int]
-            Acquisitions, net of cash acquired, and other
-        sales_maturities_of_investments : Optional[int]
-            Sales and maturities of investments.
-        purchases_of_investments : Optional[int]
-            Purchases of investments.
+        inventory : Optional[int]
+            Inventory.
+        vendor_non_trade_receivables : Optional[int]
+            Vendor non-trade receivables.
+        other_current_and_non_current_assets : Optional[int]
+            Other current and non-current assets.
+        accounts_payables : Optional[int]
+            Accounts payables.
+        deferred_revenue : Optional[int]
+            Deferred revenue.
+        other_current_and_non_current_liabilities : Optional[int]
+            Other current and non-current liabilities.
         net_cash_flow_from_operating_activities : Optional[int]
             Net cash flow from operating activities.
-        net_cash_flow_from_investing_activities : Optional[int]
-            Net cash flow from investing activities.
-        net_cash_flow_from_financing_activities : Optional[int]
-            Net cash flow from financing activities.
+        purchases_of_marketable_securities : Optional[int]
+            Purchases of investments.
+        sales_from_maturities_of_investments : Optional[int]
+            Sales and maturities of investments.
         investments_in_property_plant_and_equipment : Optional[int]
             Investments in property, plant, and equipment.
-        net_cash_used_for_investing_activities : Optional[int]
+        payments_from_acquisitions : Optional[int]
+            Acquisitions, net of cash acquired, and other
+        other_investing_activities : Optional[int]
+            Other investing activities
+        net_cash_flow_from_investing_activities : Optional[int]
             Net cash used for investing activities.
-        effect_of_forex_changes_on_cash : Optional[int]
-            Foreign currency effect on cash, cash equivalents, and restricted cash
+        taxes_paid_on_net_share_settlement : Optional[int]
+            Taxes paid on net share settlement of equity awards.
         dividends_paid : Optional[int]
             Payments for dividends and dividend equivalents
-        common_stock_issued : Optional[int]
-            Proceeds from issuance of common stock
         common_stock_repurchased : Optional[int]
             Payments related to repurchase of common stock
+        debt_proceeds : Optional[int]
+            Proceeds from issuance of term debt
         debt_repayment : Optional[int]
             Payments of long-term debt
         other_financing_activities : Optional[int]
             Other financing activities, net
+        net_cash_flow_from_financing_activities : Optional[int]
+            Net cash flow from financing activities.
         net_change_in_cash : Optional[int]
             Net increase (decrease) in cash, cash equivalents, and restricted cash
-        cash_at_end_of_period : Optional[int]
-            Cash, cash equivalents, and restricted cash at end of period
-        free_cash_flow : Optional[int]
-            Net cash flow from operating, investing and financing activities
-        operating_cash_flow : Optional[int]
-            Net cash flow from operating activities
+        reported_currency : Optional[str]
+            Reported currency in the statement. (provider: fmp)
+        filling_date : Optional[date]
+            Filling date. (provider: fmp)
+        accepted_date : Optional[datetime]
+            Accepted date. (provider: fmp)
         calendar_year : Optional[int]
-            Calendar Year (provider: fmp)
+            Calendar year. (provider: fmp)
+        change_in_working_capital : Optional[int]
+            Change in working capital. (provider: fmp)
+        other_working_capital : Optional[int]
+            Other working capital. (provider: fmp)
+        common_stock_issued : Optional[int]
+            Common stock issued. (provider: fmp)
+        effect_of_forex_changes_on_cash : Optional[int]
+            Effect of forex changes on cash. (provider: fmp)
+        cash_at_beginning_of_period : Optional[int]
+            Cash at beginning of period. (provider: fmp)
+        cash_at_end_of_period : Optional[int]
+            Cash, cash equivalents, and restricted cash at end of period (provider: fmp)
+        operating_cash_flow : Optional[int]
+            Operating cash flow. (provider: fmp)
+        capital_expenditure : Optional[int]
+            Capital expenditure. (provider: fmp)
+        free_cash_flow : Optional[int]
+            Free cash flow. (provider: fmp)
         link : Optional[str]
-            None
+            Link to the statement. (provider: fmp)
         final_link : Optional[str]
-            Final Link (provider: fmp)"""  # noqa: E501
+            Link to the final statement. (provider: fmp)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -673,7 +672,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -684,16 +682,15 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def cash_growth(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        limit: typing_extensions.Annotated[
+        limit: Annotated[
             int,
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 10,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Cash Flow Statement Growth.
@@ -704,9 +701,7 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         limit : int
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -716,7 +711,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[CashFlowStatementGrowth]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -803,7 +798,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -814,12 +808,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def comp(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Executive Compensation.
@@ -828,9 +821,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -840,7 +831,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[ExecutiveCompensation]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -886,7 +877,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -897,20 +887,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def comsplit(
         self,
-        start_date: typing_extensions.Annotated[
+        start_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="Start date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        end_date: typing_extensions.Annotated[
+        end_date: Annotated[
             Union[datetime.date, None, str],
             OpenBBCustomParameter(
                 description="End date of the data, in YYYY-MM-DD format."
             ),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Stock Split Calendar.
@@ -921,9 +910,7 @@ class CLASS_stocks_fa(Container):
             Start date of the data, in YYYY-MM-DD format.
         end_date : Union[datetime.date, NoneType, str]
             End date of the data, in YYYY-MM-DD format.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -933,7 +920,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[StockSplitCalendar]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -964,7 +951,6 @@ class CLASS_stocks_fa(Container):
                 "end_date": end_date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -975,12 +961,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def divs(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Historical Dividends.
@@ -989,9 +974,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1001,7 +984,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[HistoricalDividends]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1035,7 +1018,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1046,16 +1028,15 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def earning(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        limit: typing_extensions.Annotated[
-            Union[int, None],
+        limit: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 50,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Earnings Calendar.
@@ -1064,11 +1045,9 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        limit : Union[int, NoneType]
+        limit : Optional[int]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1078,7 +1057,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[EarningsCalendar]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1117,7 +1096,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1128,12 +1106,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def emp(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Number of Employees.
@@ -1142,9 +1119,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1154,7 +1129,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[HistoricalEmployees]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1192,7 +1167,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1203,20 +1177,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def est(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
-            Literal["quarter", "annual"],
+        period: Annotated[
+            Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        limit: typing_extensions.Annotated[
+        limit: Annotated[
             int,
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 30,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Analyst Estimates.
@@ -1225,13 +1198,11 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        period : Literal['quarter', 'annual']
+        period : Literal['annual', 'quarter']
             Period of the data to return.
         limit : int
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1241,7 +1212,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[AnalystEstimates]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1307,7 +1278,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1318,22 +1288,21 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def income(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
+        period: Annotated[
             Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        limit: typing_extensions.Annotated[
-            Union[pydantic.types.NonNegativeInt, None],
+        limit: Annotated[
+            Optional[pydantic.types.NonNegativeInt],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 12,
-        chart: bool = False,
-        provider: Union[Literal["fmp", "polygon"], None] = None,
+        provider: Optional[Literal["fmp", "intrinio", "polygon", "yfinance"]] = None,
         **kwargs
-    ) -> OBBject[List]:
+    ) -> OBBject[BaseModel]:
         """Income Statement.
 
         Parameters
@@ -1342,47 +1311,47 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         period : Literal['annual', 'quarter']
             Period of the data to return.
-        limit : Union[pydantic.types.NonNegativeInt, NoneType]
+        limit : Optional[pydantic.types.NonNegativeInt]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp', 'polygon'], NoneType]
+        provider : Optional[Literal['fmp', 'intrinio', 'polygon', 'yfinance']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
-        cik : Union[str, NoneType]
-            The CIK of the company if no symbol is provided. (provider: fmp)
-        company_name : Union[str, NoneType]
+        type : Literal['reported', 'standardized']
+            Type of the statement to be fetched. (provider: intrinio)
+        year : Optional[int]
+            Year of the statement to be fetched. (provider: intrinio)
+        company_name : Optional[str]
             Name of the company. (provider: polygon)
-        company_name_search : Union[str, NoneType]
+        company_name_search : Optional[str]
             Name of the company to search. (provider: polygon)
-        sic : Union[str, NoneType]
+        sic : Optional[str]
             The Standard Industrial Classification (SIC) of the company. (provider: polygon)
-        filing_date : Union[datetime.date, NoneType]
+        filing_date : Optional[datetime.date]
             Filing date of the financial statement. (provider: polygon)
-        filing_date_lt : Union[datetime.date, NoneType]
+        filing_date_lt : Optional[datetime.date]
             Filing date less than the given date. (provider: polygon)
-        filing_date_lte : Union[datetime.date, NoneType]
+        filing_date_lte : Optional[datetime.date]
             Filing date less than or equal to the given date. (provider: polygon)
-        filing_date_gt : Union[datetime.date, NoneType]
+        filing_date_gt : Optional[datetime.date]
             Filing date greater than the given date. (provider: polygon)
-        filing_date_gte : Union[datetime.date, NoneType]
+        filing_date_gte : Optional[datetime.date]
             Filing date greater than or equal to the given date. (provider: polygon)
-        period_of_report_date : Union[datetime.date, NoneType]
+        period_of_report_date : Optional[datetime.date]
             Period of report date of the financial statement. (provider: polygon)
-        period_of_report_date_lt : Union[datetime.date, NoneType]
+        period_of_report_date_lt : Optional[datetime.date]
             Period of report date less than the given date. (provider: polygon)
-        period_of_report_date_lte : Union[datetime.date, NoneType]
+        period_of_report_date_lte : Optional[datetime.date]
             Period of report date less than or equal to the given date. (provider: polygon)
-        period_of_report_date_gt : Union[datetime.date, NoneType]
+        period_of_report_date_gt : Optional[datetime.date]
             Period of report date greater than the given date. (provider: polygon)
-        period_of_report_date_gte : Union[datetime.date, NoneType]
+        period_of_report_date_gte : Optional[datetime.date]
             Period of report date greater than or equal to the given date. (provider: polygon)
-        include_sources : Union[bool, NoneType]
+        include_sources : Optional[bool]
             Whether to include the sources of the financial statement. (provider: polygon)
-        order : Union[Literal['asc', 'desc'], NoneType]
+        order : Optional[Literal['asc', 'desc']]
             Order of the financial statement. (provider: polygon)
-        sort : Union[Literal['filing_date', 'period_of_report_date'], NoneType]
+        sort : Optional[Literal['filing_date', 'period_of_report_date']]
             Sort of the financial statement. (provider: polygon)
 
         Returns
@@ -1390,7 +1359,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[IncomeStatement]
                 Serializable results.
-            provider : Union[Literal['fmp', 'polygon'], NoneType]
+            provider : Optional[Literal['fmp', 'intrinio', 'polygon', 'yfinance']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1401,22 +1370,14 @@ class CLASS_stocks_fa(Container):
 
         IncomeStatement
         ---------------
+        symbol : Optional[str]
+            Symbol to get data for.
         date : Optional[date]
             Date of the income statement.
-        symbol : Optional[str]
-            Symbol of the company.
-        cik : Optional[str]
-            Central Index Key.
-        currency : Optional[str]
-            Reporting currency.
-        filing_date : Optional[date]
-            Filling date.
-        accepted_date : Optional[datetime]
-            Accepted date.
-        calendar_year : Optional[int]
-            Calendar year.
         period : Optional[str]
             Period of the income statement.
+        cik : Optional[str]
+            Central Index Key.
         revenue : Optional[int]
             Revenue.
         cost_of_revenue : Optional[int]
@@ -1473,24 +1434,26 @@ class CLASS_stocks_fa(Container):
             Weighted average shares outstanding.
         weighted_average_shares_outstanding_dil : Optional[int]
             Weighted average shares outstanding diluted.
-        link : Optional[str]
-            Link to the income statement.
-        final_link : Optional[str]
-            Final link to the income statement.
+        income_loss_from_continuing_operations_before_tax : Optional[float]
+            Income/Loss From Continuing Operations After Tax (provider: polygon)
         income_loss_from_continuing_operations_after_tax : Optional[float]
-            None
+            Income/Loss From Continuing Operations After Tax (provider: polygon)
         benefits_costs_expenses : Optional[float]
-            None
-        net_income_loss_attributable_to_noncontrolling_interest : Optional[int]
-            None
+            Benefits, Costs And Expenses (provider: polygon)
+        net_income_loss_attributable_to_noncontrolling_interest : Optional[float]
+            Net Income/Loss Attributable To Noncontrolling Interest (provider: polygon)
         net_income_loss_attributable_to_parent : Optional[float]
-            None
-        net_income_loss_available_to_common_stockholders_basic : Optional[float]
-            None
+            Net Income/Loss Attributable To Parent (provider: polygon)
+        income_tax_expense_benefit_deferred : Optional[float]
+            Income Tax Expense/Benefit Deferred (provider: polygon)
         participating_securities_distributed_and_undistributed_earnings_loss_basic : Optional[float]
-            None
+            Participating Securities Distributed And Undistributed Earnings Loss Basic (provider: polygon)
+        net_income_loss_available_to_common_stockholders_basic : Optional[float]
+            Net Income/Loss Available To Common Stockholders Basic (provider: polygon)
+        nonoperating_income_loss : Optional[float]
+            Nonoperating Income Loss (provider: polygon)
         preferred_stock_dividends_and_other_adjustments : Optional[float]
-            None"""  # noqa: E501
+            Preferred Stock Dividends And Other Adjustments (provider: polygon)"""  # noqa: E501
 
         inputs = filter_inputs(
             provider_choices={
@@ -1502,7 +1465,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1513,20 +1475,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def income_growth(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        limit: typing_extensions.Annotated[
+        limit: Annotated[
             int,
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 10,
-        period: typing_extensions.Annotated[
+        period: Annotated[
             Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Income Statement Growth.
@@ -1539,9 +1500,7 @@ class CLASS_stocks_fa(Container):
             The number of data entries to return.
         period : Literal['annual', 'quarter']
             Period of the data to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1551,7 +1510,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[IncomeStatementGrowth]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1631,7 +1590,6 @@ class CLASS_stocks_fa(Container):
                 "period": period,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1642,12 +1600,12 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def ins(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        transactionType: typing_extensions.Annotated[
-            Union[
+        transactionType: Annotated[
+            Optional[
                 List[
                     Literal[
                         "A-Award",
@@ -1669,25 +1627,23 @@ class CLASS_stocks_fa(Container):
                         "X-InTheMoney",
                         "Z-Trust",
                     ]
-                ],
-                None,
+                ]
             ],
             OpenBBCustomParameter(description="Type of the transaction."),
         ] = ["P-Purchase"],
-        reportingCik: typing_extensions.Annotated[
-            Union[int, None],
+        reportingCik: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="CIK of the reporting owner."),
         ] = None,
-        companyCik: typing_extensions.Annotated[
-            Union[int, None],
+        companyCik: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="CIK of the company owner."),
         ] = None,
-        page: typing_extensions.Annotated[
-            Union[int, None],
+        page: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="Page number of the data to fetch."),
         ] = 0,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Stock Insider Trading.
@@ -1696,17 +1652,15 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        transactionType : Union[List[Literal['A-Award', 'C-Conversion', 'D-Return', 'E-ExpireShort', 'F-InKind', 'G-Gift', 'H-ExpireLong', 'I-Discretionary', 'J-Other', 'L-Small', 'M-Exempt', 'O-OutOfTheMoney', 'P-Purchase', 'S-Sale', 'U-Tender', 'W-Will', 'X-InTheMoney', 'Z-Trust']], NoneType]
+        transactionType : Optional[List[Literal['A-Award', 'C-Conversion', 'D-Return', 'E-ExpireShort', 'F-InKind', 'G-Gift', 'H-ExpireLong', 'I-Discretionary', 'J-Other', 'L-Small', 'M-Exempt', 'O-OutOfTheMoney', 'P-Purchase', 'S-Sale', 'U-Tender', 'W-Will', 'X-InTheMoney', 'Z-Trust']]]
             Type of the transaction.
-        reportingCik : Union[int, NoneType]
+        reportingCik : Optional[int]
             CIK of the reporting owner.
-        companyCik : Union[int, NoneType]
+        companyCik : Optional[int]
             CIK of the company owner.
-        page : Union[int, NoneType]
+        page : Optional[int]
             Page number of the data to fetch.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1716,7 +1670,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[StockInsiderTrading]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1770,7 +1724,6 @@ class CLASS_stocks_fa(Container):
                 "page": page,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1781,19 +1734,18 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def ins_own(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        include_current_quarter: typing_extensions.Annotated[
+        include_current_quarter: Annotated[
             bool, OpenBBCustomParameter(description="Include current quarter data.")
         ] = False,
-        date: typing_extensions.Annotated[
-            Union[datetime.date, None],
+        date: Annotated[
+            Optional[datetime.date],
             OpenBBCustomParameter(description="A specific date to get data for."),
         ] = None,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Institutional Ownership.
@@ -1804,11 +1756,9 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         include_current_quarter : bool
             Include current quarter data.
-        date : Union[datetime.date, NoneType]
+        date : Optional[datetime.date]
             A specific date to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1818,7 +1768,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[InstitutionalOwnership]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -1913,7 +1863,6 @@ class CLASS_stocks_fa(Container):
                 "date": date,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -1924,20 +1873,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def metrics(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
+        period: Annotated[
             Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        limit: typing_extensions.Annotated[
-            Union[int, None],
+        limit: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 100,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Key Metrics.
@@ -1948,11 +1896,9 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         period : Literal['annual', 'quarter']
             Period of the data to return.
-        limit : Union[int, NoneType]
+        limit : Optional[int]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -1962,7 +1908,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[KeyMetrics]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2104,7 +2050,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2115,12 +2060,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def mgmt(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Key Executives.
@@ -2129,9 +2073,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2141,7 +2083,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[KeyExecutives]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2175,7 +2117,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2186,12 +2127,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def overview(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[BaseModel]:
         """Company Overview.
@@ -2200,9 +2140,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2212,7 +2150,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[CompanyOverview]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2304,7 +2242,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2315,20 +2252,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def own(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        date: typing_extensions.Annotated[
-            Union[datetime.date, None],
+        date: Annotated[
+            Optional[datetime.date],
             OpenBBCustomParameter(description="A specific date to get data for."),
         ] = None,
-        page: typing_extensions.Annotated[
-            Union[int, None],
+        page: Annotated[
+            Optional[int],
             OpenBBCustomParameter(description="Page number of the data to fetch."),
         ] = 0,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Stock Ownership.
@@ -2337,13 +2273,11 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        date : Union[datetime.date, NoneType]
+        date : Optional[datetime.date]
             A specific date to get data for.
-        page : Union[int, NoneType]
+        page : Optional[int]
             Page number of the data to fetch.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2353,7 +2287,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[StockOwnership]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2453,7 +2387,6 @@ class CLASS_stocks_fa(Container):
                 "page": page,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2464,12 +2397,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def pt(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[BaseModel]:
         """Price Target Consensus.
@@ -2478,9 +2410,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2490,7 +2420,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[PriceTargetConsensus]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2520,7 +2450,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2531,12 +2460,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def pta(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Price Target.
@@ -2545,9 +2473,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2559,7 +2485,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[PriceTarget]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2607,7 +2533,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2618,20 +2543,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def ratios(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
+        period: Annotated[
             Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        limit: typing_extensions.Annotated[
-            Union[pydantic.types.NonNegativeInt, None],
+        limit: Annotated[
+            Optional[pydantic.types.NonNegativeInt],
             OpenBBCustomParameter(description="The number of data entries to return."),
         ] = 12,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Extensive set of ratios over time.
@@ -2642,11 +2566,9 @@ class CLASS_stocks_fa(Container):
             Symbol to get data for.
         period : Literal['annual', 'quarter']
             Period of the data to return.
-        limit : Union[pydantic.types.NonNegativeInt, NoneType]
+        limit : Optional[pydantic.types.NonNegativeInt]
             The number of data entries to return.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2656,7 +2578,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[FinancialRatios]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2792,7 +2714,6 @@ class CLASS_stocks_fa(Container):
                 "limit": limit,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2803,20 +2724,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def revgeo(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
-            Literal["quarter", "annual"],
+        period: Annotated[
+            Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        structure: typing_extensions.Annotated[
+        structure: Annotated[
             Literal["hierarchical", "flat"],
             OpenBBCustomParameter(description="Structure of the returned data."),
         ] = "flat",
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Revenue Geographic.
@@ -2825,13 +2745,11 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        period : Literal['quarter', 'annual']
+        period : Literal['annual', 'quarter']
             Period of the data to return.
         structure : Literal['hierarchical', 'flat']
             Structure of the returned data.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2841,7 +2759,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[RevenueGeographic]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2877,7 +2795,6 @@ class CLASS_stocks_fa(Container):
                 "structure": structure,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2888,20 +2805,19 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def revseg(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        period: typing_extensions.Annotated[
-            Literal["quarter", "annual"],
+        period: Annotated[
+            Literal["annual", "quarter"],
             OpenBBCustomParameter(description="Period of the data to return."),
         ] = "annual",
-        structure: typing_extensions.Annotated[
+        structure: Annotated[
             Literal["hierarchical", "flat"],
             OpenBBCustomParameter(description="Structure of the returned data."),
         ] = "flat",
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Revenue Business Line.
@@ -2910,13 +2826,11 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        period : Literal['quarter', 'annual']
+        period : Literal['annual', 'quarter']
             Period of the data to return.
         structure : Literal['hierarchical', 'flat']
             Structure of the returned data.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2926,7 +2840,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[RevenueBusinessLine]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -2952,7 +2866,6 @@ class CLASS_stocks_fa(Container):
                 "structure": structure,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -2963,12 +2876,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def shrs(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Share Statistics.
@@ -2977,9 +2889,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -2989,7 +2899,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[ShareStatistics]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -3021,7 +2931,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -3032,12 +2941,11 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def split(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Historical Stock Splits.
@@ -3046,9 +2954,7 @@ class CLASS_stocks_fa(Container):
         ----------
         symbol : Union[str, List[str]]
             Symbol to get data for.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -3058,7 +2964,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[HistoricalStockSplits]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -3086,7 +2992,6 @@ class CLASS_stocks_fa(Container):
                 "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
@@ -3097,22 +3002,21 @@ class CLASS_stocks_fa(Container):
     @validate_arguments
     def transcript(
         self,
-        symbol: typing_extensions.Annotated[
+        symbol: Annotated[
             Union[str, List[str]],
             OpenBBCustomParameter(description="Symbol to get data for."),
         ],
-        year: typing_extensions.Annotated[
+        year: Annotated[
             int,
             OpenBBCustomParameter(description="Year of the earnings call transcript."),
         ],
-        quarter: typing_extensions.Annotated[
+        quarter: Annotated[
             Literal[1, 2, 3, 4],
             OpenBBCustomParameter(
                 description="Quarter of the earnings call transcript."
             ),
         ] = 1,
-        chart: bool = False,
-        provider: Union[Literal["fmp"], None] = None,
+        provider: Optional[Literal["fmp"]] = None,
         **kwargs
     ) -> OBBject[List]:
         """Earnings Call Transcript.
@@ -3125,9 +3029,7 @@ class CLASS_stocks_fa(Container):
             Year of the earnings call transcript.
         quarter : Literal[1, 2, 3, 4]
             Quarter of the earnings call transcript.
-        chart : bool
-            Whether to create a chart or not, by default False.
-        provider : Union[Literal['fmp'], NoneType]
+        provider : Optional[Literal['fmp']]
             The provider to use for the query, by default None.
             If None, the provider specified in defaults is selected or 'fmp' if there is
             no default.
@@ -3137,7 +3039,7 @@ class CLASS_stocks_fa(Container):
         OBBject
             results : List[EarningsCallTranscript]
                 Serializable results.
-            provider : Union[Literal['fmp'], NoneType]
+            provider : Optional[Literal['fmp']]
                 Provider name.
             warnings : Optional[List[Warning_]]
                 List of warnings.
@@ -3169,7 +3071,6 @@ class CLASS_stocks_fa(Container):
                 "quarter": quarter,
             },
             extra_params=kwargs,
-            chart=chart,
         )
 
         return self._command_runner.run(
diff --git a/openbb_sdk/openbb/package/stocks_options.py b/openbb_sdk/openbb/package/stocks_options.py
new file mode 100644
index 00000000000..545fe5f3112
--- /dev/null
+++ b/openbb_sdk/openbb/package/stocks_options.py
@@ -0,0 +1,147 @@
+### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
+
+from typing import List, Literal, Optional, Union
+
+from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
+from openbb_core.app.model.obbject import OBBject
+from openbb_core.app.static.container import Container
+from openbb_core.app.static.filters import filter_inputs
+from pydantic import validate_arguments
+from typing_extensions import Annotated
+
+
+class CLASS_stocks_options(Container):
+    """/stocks/options
+    chains
+    """
+
+    def __repr__(self) -> str:
+        return self.__doc__ or ""
+
+    @validate_arguments
+    def chains(
+        self,
+        symbol: Annotated[
+            Union[str, List[str]],
+            OpenBBCustomParameter(description="Symbol to get data for."),
+        ],
+        provider: Optional[Literal["cboe", "intrinio"]] = None,
+        **kwargs
+    ) -> OBBject[List]:
+        """Get the complete options chain for a ticker.
+
+        Parameters
+        ----------
+        symbol : Union[str, List[str]]
+            Symbol to get data for.
+        provider : Optional[Literal['cboe', 'intrinio']]
+            The provider to use for the query, by default None.
+            If None, the provider specified in defaults is selected or 'cboe' if there is
+            no default.
+        date : Union[datetime.date, str, NoneType]
+            Date for which the options chains are returned. (provider: intrinio)
+
+        Returns
+        -------
+        OBBject
+            results : List[OptionsChains]
+                Serializable results.
+            provider : Optional[Literal['cboe', 'intrinio']]
+                Provider name.
+            warnings : Optional[List[Warning_]]
+                List of warnings.
+            chart : Optional[Chart]
+                Chart object.
+            metadata: Optional[Metadata]
+                Metadata info about the command execution.
+
+        OptionsChains
+        -------------
+        expiration : Optional[datetime]
+            Expiration date of the contract.
+        strike : Optional[float]
+            Strike price of the contract.
+        option_type : Optional[str]
+            Call or Put.
+        contract_symbol : Optional[str]
+            Contract symbol for the option.
+        bid : Optional[float]
+            Bid price of the contract.
+        ask : Optional[float]
+            Ask price of the contract.
+        open_interest : Optional[float]
+            Open interest on the contract.
+        volume : Optional[float]
+            Current trading volume on the contract.
+        bid_size : Optional[int]
+            Bid size for the option. (provider: cboe)
+        ask_size : Optional[int]
+            Ask size for the option. (provider: cboe)
+        theoretical : Optional[float]
+            Theoretical value of the option. (provider: cboe)
+        open : Optional[float]
+            Opening price of the option. (provider: cboe)
+        high : Optional[float]
+            High price of the option. (provider: cboe)
+        low : Optional[float]
+            Low price of the option. (provider: cboe)
+        last_trade_price : Optional[float]
+            Last trade price of the option. (provider: cboe)
+        tick : Optional[str]
+            Whether the last tick was up or down in price. (provider: cboe)
+        prev_close : Optional[float]
+            Previous closing price of the option. (provider: cboe)
+        change : Optional[float]
+            Change in  price of the option. (provider: cboe)
+        change_percent : Optional[float]
+            Change, in percent, of the option. (provider: cboe)
+        implied_volatility : Optional[float]
+            Implied volatility of the option. (provider: cboe)
+        delta : Optional[float]
+            Delta of the option. (provider: cboe)
+        gamma : Optional[float]
+            Gamma of the option. (provider: cboe)
+        vega : Optional[float]
+            Vega of the option. (provider: cboe)
+        theta : Optional[float]
+            Theta of the option. (provider: cboe)
+        rho : Optional[float]
+            Rho of the option. (provider: cboe)
+        last_trade_timestamp : Optional[datetime]
+            Last trade timestamp of the option. (provider: cboe)
+        dte : Optional[int]
+            Days to expiration for the option. (provider: cboe)
+        mark : Optional[float]
+            The mid-price between the latest bid-ask spread. (provider: intrinio)
+        open_bid : Optional[float]
+            The lowest bid price for the option that day. (provider: intrinio)
+        open_ask : Optional[float]
+            The lowest ask price for the option that day. (provider: intrinio)
+        bid_low : Optional[float]
+            The lowest bid price for the option that day. (provider: intrinio)
+        ask_low : Optional[float]
+            The lowest ask price for the option that day. (provider: intrinio)
+        bid_high : Optional[float]
+            The highest bid price for the option that day. (provider: intrinio)
+        ask_high : Optional[float]
+            The highest ask price for the option that day. (provider: intrinio)
+        close : Optional[float]
+            The close price for the option that day. (provider: intrinio)
+        eod_date : Optional[date]
+            Historical date for which the options chains data is from. (provider: intrinio)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            provider_choices={
+                "provider": provider,
+            },
+            standard_params={
+                "symbol": ",".join(symbol) if isinstance(symbol, list) else symbol,
+            },
+            extra_params=kwargs,
+        )
+
+        return self._command_runner.run(
+            "/stocks/options/chains",
+            **inputs,
+        )
diff --git a/openbb_sdk/openbb/package/ta.py b/openbb_sdk/openbb/package/ta.py
new file mode 100644
index 00000000000..3cfc2d7a1e8
--- /dev/null
+++ b/openbb_sdk/openbb/package/ta.py
@@ -0,0 +1,1486 @@
+### THIS FILE IS AUTO-GENERATED. DO NOT EDIT. ###
+
+from typing import List, Literal, Optional, Union
+
+import openbb_provider
+import pandas
+import pydantic
+import pydantic.types
+from openbb_core.app.model.obbject import OBBject
+from openbb_core.app.static.container import Container
+from openbb_core.app.static.filters import filter_inputs
+from pydantic import validate_arguments
+
+
+class CLASS_ta(Container):
+    """/ta
+    ad
+    adosc
+    adx
+    aroon
+    atr
+    bbands
+    cci
+    cg
+    clenow
+    cones
+    demark
+    donchian
+    ema
+    fib
+    fisher
+    hma
+    ichimoku
+    kc
+    macd
+    obv
+    rsi
+    sma
+    stoch
+    vwap
+    wma
+    zlma
+    """
+
+    def __repr__(self) -> str:
+        return self.__doc__ or ""
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def ad(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+        The Accumulation/Distribution Line is similar to the On Balance
+        Volume (OBV), which sums the volume times +1/-1 based on whether the close is
+        higher than the previous close. The Accumulation/Distribution indicator, however
+        multiplies the volume by the close location value (CLV). The CLV is based on the
+        movement of the issue within a single bar and can be +1, -1 or zero.
+
+
+        The Accumulation/Distribution Line is interpreted by looking for a divergence in
+        the direction of the indicator relative to price. If the Accumulation/Distribution
+        Line is trending upward it indicates that the price may follow. Also, if the
+        Accumulation/Distribution Line becomes flat while the price is still rising (or falling)
+        then it signals an impending flattening of the price.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        offset : int, optional
+            Offset of the AD, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> ad_data = obb.ta.ad(data=stock_data.results,offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/ad",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def adosc(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        fast: pydantic.types.PositiveInt = 3,
+        slow: pydantic.types.PositiveInt = 10,
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+        Accumulation/Distribution Oscillator, also known as the Chaikin Oscillator
+        is essentially a momentum indicator, but of the Accumulation-Distribution line
+        rather than merely price. It looks at both the strength of price moves and the
+        underlying buying and selling pressure during a given time period. The oscillator
+        reading above zero indicates net buying pressure, while one below zero registers
+        net selling pressure. Divergence between the indicator and pure price moves are
+        the most common signals from the indicator, and often flag market turning points.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        fast : PositiveInt, optional
+            Number of periods to be used for the fast calculation, by default 3.
+        slow : PositiveInt, optional
+            Number of periods to be used for the slow calculation, by default 10.
+        offset : int, optional
+            Offset to be used for the calculation, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> adosc_data = obb.ta.adosc(data=stock_data.results, fast=3, slow=10, offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            fast=fast,
+            slow=slow,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/adosc",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def adx(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: int = 50,
+        scalar: float = 100.0,
+        drift: int = 1,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        The ADX is a Welles Wilder style moving average of the Directional Movement Index (DX).
+        The values range from 0 to 100, but rarely get above 60. To interpret the ADX, consider
+        a high number to be a strong trend, and a low number, a weak trend.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        length : int, optional
+            Number of periods for the ADX, by default 50.
+        scalar : float, optional
+            Scalar value for the ADX, by default 100.0.
+        drift : int, optional
+            Drift value for the ADX, by default 1.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> adx_data = obb.ta.adx(data=stock_data.results,length=50,scalar=100.0,drift=1)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+            scalar=scalar,
+            drift=drift,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/adx",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def aroon(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: int = 25,
+        scalar: int = 100,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+           The word aroon is Sanskrit for "dawn's early light." The Aroon
+           indicator attempts to show when a new trend is dawning. The indicator consists
+           of two lines (Up and Down) that measure how long it has been since the highest
+           high/lowest low has occurred within an n period range.
+
+        When the Aroon Up is
+           staying between 70 and 100 then it indicates an upward trend. When the Aroon Down
+           is staying between 70 and 100 then it indicates an downward trend. A strong upward
+           trend is indicated when the Aroon Up is above 70 while the Aroon Down is below 30.
+           Likewise, a strong downward trend is indicated when the Aroon Down is above 70 while
+           the Aroon Up is below 30. Also look for crossovers. When the Aroon Down crosses above
+           the Aroon Up, it indicates a weakening of the upward trend (and vice versa).
+
+           Parameters
+           ----------
+           data : List[Data]
+               List of data to be used for the calculation.
+           index: str, optional
+               Index column name to use with `data`, by default "date".
+           length : int, optional
+               Number of periods to be used for the calculation, by default 25.
+           scalar : int, optional
+               Scalar to be used for the calculation, by default 100.
+
+           Returns
+           -------
+           OBBject[List[Data]]
+               The calculated data.
+
+           Examples
+           --------
+           >>> from openbb import obb
+           >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+           >>> aroon_data = obb.ta.aroon(data=stock_data.results, length=25, scalar=100)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+            scalar=scalar,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/aroon",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def atr(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: pydantic.types.PositiveInt = 14,
+        mamode: Literal["rma", "ema", "sma", "wma"] = "rma",
+        drift: pydantic.types.NonNegativeInt = 1,
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+        Average True Range is used to measure volatility, especially volatility caused by
+        gaps or limit moves.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to apply the indicator to.
+        index : str, optional
+            Index column name, by default "date"
+        length : PositiveInt, optional
+            It's period, by default 14
+        mamode : Literal["rma", "ema", "sma", "wma"], optional
+            Moving average mode, by default "rma"
+        drift : NonNegativeInt, optional
+            The difference period, by default 1
+        offset : int, optional
+            How many periods to offset the result, by default 0
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            List of data with the indicator applied.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> atr_data = obb.ta.atr(data=stock_data.results)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+            mamode=mamode,
+            drift=drift,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/atr",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def bbands(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 50,
+        std: pydantic.types.NonNegativeFloat = 2,
+        mamode: Literal["sma", "ema", "wma", "rma"] = "sma",
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+            Bollinger Bands consist of three lines. The middle band is a simple
+            moving average (generally 20 periods) of the typical price (TP). The upper and lower
+            bands are F standard deviations (generally 2) above and below the middle band.
+            The bands widen and narrow when the volatility of the price is higher or lower,
+            respectively.
+
+        Bollinger Bands do not, in themselves, generate buy or sell signals;
+            they are an indicator of overbought or oversold conditions. When the price is near the
+            upper or lower band it indicates that a reversal may be imminent. The middle band
+            becomes a support or resistance level. The upper and lower bands can also be
+            interpreted as price targets. When the price bounces off of the lower band and crosses
+            the middle band, then the upper band becomes the price target.
+
+            Parameters
+            ----------
+            data : List[Data]
+                List of data to be used for the calculation.
+            target : str
+                Target column name.
+            index : str, optional
+                Index column name to use with `data`, by default "date".
+            length : int, optional
+                Number of periods to be used for the calculation, by default 50.
+            std : NonNegativeFloat, optional
+                Standard deviation to be used for the calculation, by default 2.
+            mamode : Literal["sma", "ema", "wma", "rma"], optional
+                Moving average mode to be used for the calculation, by default "sma".
+            offset : int, optional
+                Offset to be used for the calculation, by default 0.
+
+            Returns
+            -------
+            OBBject[List[Data]]
+                The calculated data.
+
+            Examples
+            --------
+            >>> from openbb import obb
+            >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+            >>> bbands = obb.ta.bbands(
+            >>>     data=stock_data.results, target="close", length=50, std=2, mamode="sma", offset=0
+            >>> )
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            std=std,
+            mamode=mamode,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/bbands",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def cci(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: pydantic.types.PositiveInt = 14,
+        scalar: pydantic.types.PositiveFloat = 0.015,
+    ) -> OBBject[List]:
+        """
+        The CCI is designed to detect beginning and ending market trends.
+        The range of 100 to -100 is the normal trading range. CCI values outside of this
+        range indicate overbought or oversold conditions. You can also look for price
+        divergence in the CCI. If the price is making new highs, and the CCI is not,
+        then a price correction is likely.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the CCI calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        length : PositiveInt, optional
+            The length of the CCI, by default 14.
+        scalar : PositiveFloat, optional
+            The scalar of the CCI, by default 0.015.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The CCI data.
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+            scalar=scalar,
+        )
+
+        return self._command_runner.run(
+            "/ta/cci",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def cg(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: pydantic.types.PositiveInt = 14,
+    ) -> OBBject[List]:
+        """
+        The Center of Gravity indicator, in short, is used to anticipate future price movements
+        and to trade on price reversals as soon as they happen. However, just like other oscillators,
+        the COG indicator returns the best results in range-bound markets and should be avoided when
+        the price is trending. Traders who use it will be able to closely speculate the upcoming
+        price change of the asset.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the COG calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date"
+        length : PositiveInt, optional
+            The length of the COG, by default 14
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The COG data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> cg_data = obb.ta.cg(data=stock_data.results, length=14)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+        )
+
+        return self._command_runner.run(
+            "/ta/cg",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def clenow(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        target: str = "adj_close",
+        period: pydantic.types.PositiveInt = 90,
+    ) -> OBBject[List]:
+        """
+        Clenow Volatility Adjusted Momentum.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        target : str, optional
+            Target column name, by default "adj_close".
+        period : PositiveInt, optional
+            Number of periods for the momentum, by default 90.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> clenow_data = obb.ta.clenow(data=stock_data.results,period=90)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            target=target,
+            period=period,
+        )
+
+        return self._command_runner.run(
+            "/ta/clenow",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def cones(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        lower_q: float = 0.25,
+        upper_q: float = 0.75,
+        model: Literal[
+            "STD",
+            "Parkinson",
+            "Garman-Klass",
+            "Hodges-Tompkins",
+            "Rogers-Satchell",
+            "Yang-Zhang",
+        ] = "STD",
+        is_crypto: bool = False,
+    ) -> OBBject[List]:
+        """Calculate the realized volatility quantiles over rolling windows of time.
+
+        The model for calculating volatility is selectable.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date"
+        lower_q : float, optional
+            The lower quantile value for calculations
+        upper_q : float, optional
+            The upper quantile value for calculations
+        model : Literal["STD", "Parkinson", "Garman-Klass", "Hodges-Tompkins", "Rogers-Satchell", "Yang-Zhang"], optional
+            The model used to calculate realized volatility
+
+                Standard deviation measures how widely returns are dispersed from the average return.
+                It is the most common (and biased) estimator of volatility.
+
+                Parkinson volatility uses the high and low price of the day rather than just close to close prices.
+                It is useful for capturing large price movements during the day.
+
+                Garman-Klass volatility extends Parkinson volatility by taking into account the opening and closing price.
+                As markets are most active during the opening and closing of a trading session;
+                it makes volatility estimation more accurate.
+
+                Hodges-Tompkins volatility is a bias correction for estimation using an overlapping data sample.
+                It produces unbiased estimates and a substantial gain in efficiency.
+
+                Rogers-Satchell is an estimator for measuring the volatility with an average return not equal to zero.
+                Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term,
+                mean return not equal to zero.
+
+                Yang-Zhang volatility is the combination of the overnight (close-to-open volatility).
+                It is a weighted average of the Rogers-Satchell volatility and the open-to-close volatility.
+        is_crypto : bool, optional
+            Whether the data is crypto or not. If True, volatility is calculated for 365 days instead of 252
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The cones data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> cones_data = obb.ta.cones(data=stock_data.results, lower_q=0.25, upper_q=0.75, model="STD")
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            lower_q=lower_q,
+            upper_q=upper_q,
+            model=model,
+            is_crypto=is_crypto,
+        )
+
+        return self._command_runner.run(
+            "/ta/cones",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def demark(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        target: str = "close",
+        show_all: bool = False,
+        asint: bool = False,
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+        Demark sequential indicator
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        target : str, optional
+            Target column name, by default "close".
+        show_all : bool, optional
+            Show 1 - 13. If set to False, show 6 - 9
+        asint : bool, optional
+            If True, fill NAs with 0 and change type to int, by default False
+        offset : int, optional
+            How many periods to offset the result
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> demark_data = obb.ta.demark(data=stock_data.results,offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            target=target,
+            show_all=show_all,
+            asint=asint,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/demark",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def donchian(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        lower_length: pydantic.types.PositiveInt = 20,
+        upper_length: pydantic.types.PositiveInt = 20,
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+        Donchian Channels are three lines generated by moving average
+        calculations that comprise an indicator formed by upper and lower
+        bands around a midrange or median band. The upper band marks the
+        highest price of a security over N periods while the lower band
+        marks the lowest price of a security over N periods. The area
+        between the upper and lower bands represents the Donchian Channel.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        lower_length : PositiveInt, optional
+            Number of periods for the lower band, by default 20.
+        upper_length : PositiveInt, optional
+            Number of periods for the upper band, by default 20.
+        offset : int, optional
+            Offset of the Donchian Channel, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> donchian_data = obb.ta.donchian(data=stock_data.results,lower_length=20,upper_length=20,offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            lower_length=lower_length,
+            upper_length=upper_length,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/donchian",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def ema(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 50,
+        offset: int = 0,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        The Exponential Moving Average is a staple of technical
+        analysis and is used in countless technical indicators. In a Simple Moving
+        Average, each value in the time period carries equal weight, and values outside
+        of the time period are not included in the average. However, the Exponential
+        Moving Average is a cumulative calculation, including all data. Past values have
+        a diminishing contribution to the average, while more recent values have a greater
+        contribution. This method allows the moving average to be more responsive to changes
+        in the data.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the calculation.
+        target : str
+            Target column name.
+        index : str, optional
+            Index column name to use with `data`, by default "date"
+        length : int, optional
+            The length of the calculation, by default 50.
+        offset : int, optional
+            The offset of the calculation, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> ema_data = obb.ta.ema(data=stock_data.results,target="close",length=50,offset=0)
+
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            offset=offset,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/ema",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def fib(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        close_column: Literal["close", "adj_close"] = "close",
+        period: pydantic.types.PositiveInt = 120,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+    ) -> OBBject[List]:
+        """Create Fibonacci Retracement Levels.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to apply the indicator to.
+        index : str, optional
+            Index column name, by default "date"
+        period : PositiveInt, optional
+            Period to calculate the indicator, by default 120
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            List of data with the indicator applied.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> fib_data = obb.ta.fib(data=stock_data.results, period=120)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            close_column=close_column,
+            period=period,
+            start_date=start_date,
+            end_date=end_date,
+        )
+
+        return self._command_runner.run(
+            "/ta/fib",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def fisher(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: pydantic.types.PositiveInt = 14,
+        signal: pydantic.types.PositiveInt = 1,
+    ) -> OBBject[List]:
+        """
+        The Fisher Transform is a technical indicator created by John F. Ehlers
+        that converts prices into a Gaussian normal distribution.1 The indicator
+        highlights when prices have   moved to an extreme, based on recent prices.
+        This may help in spotting turning points in the price of an asset. It also
+        helps show the trend and isolate the price waves within a trend.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to apply the indicator to.
+        index : str, optional
+            Index column name, by default "date"
+        length : PositiveInt, optional
+            Fisher period, by default 14
+        signal : PositiveInt, optional
+            Fisher Signal period, by default 1
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            List of data with the indicator applied.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> fisher_data = obb.ta.fisher(data=stock_data.results, length=14, signal=1)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+            signal=signal,
+        )
+
+        return self._command_runner.run(
+            "/ta/fisher",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def hma(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 50,
+        offset: int = 0,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        The Hull Moving Average solves the age old dilemma of making a moving average
+        more responsive to current price activity whilst maintaining curve smoothness.
+        In fact the HMA almost eliminates lag altogether and manages to improve smoothing
+        at the same time.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        target : str
+            Target column name.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        length : int, optional
+            Number of periods for the HMA, by default 50.
+        offset : int, optional
+            Offset of the HMA, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> hma_data = obb.ta.hma(data=stock_data.results,target="close",length=50,offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            offset=offset,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/hma",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def ichimoku(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        conversion: pydantic.types.PositiveInt = 9,
+        base: pydantic.types.PositiveInt = 26,
+        lagging: pydantic.types.PositiveInt = 52,
+        offset: pydantic.types.PositiveInt = 26,
+        lookahead: bool = False,
+    ) -> OBBject[List]:
+        """
+        The Ichimoku Cloud, also known as Ichimoku Kinko Hyo, is a versatile indicator that
+        defines support and resistance, identifies trend direction, gauges momentum and provides
+        trading signals. Ichimoku Kinko Hyo translates into "one look equilibrium chart". With
+        one look, chartists can identify the trend and look for potential signals within that trend.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        conversion : PositiveInt, optional
+            Number of periods for the conversion line, by default 9.
+        base : PositiveInt, optional
+            Number of periods for the base line, by default 26.
+        lagging : PositiveInt, optional
+            Number of periods for the lagging span, by default 52.
+        offset : PositiveInt, optional
+            Number of periods for the offset, by default 26.
+        lookahead : bool, optional
+            drops the Chikou Span Column to prevent potential data leak
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            conversion=conversion,
+            base=base,
+            lagging=lagging,
+            offset=offset,
+            lookahead=lookahead,
+        )
+
+        return self._command_runner.run(
+            "/ta/ichimoku",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def kc(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        length: pydantic.types.PositiveInt = 20,
+        scalar: pydantic.types.PositiveFloat = 20,
+        mamode: Literal["ema", "sma", "wma", "hma", "zlma"] = "ema",
+        offset: pydantic.types.NonNegativeInt = 0,
+    ) -> OBBject[List]:
+        """
+        Keltner Channels are volatility-based bands that are placed
+        on either side of an asset's price and can aid in determining
+        the direction of a trend.The Keltner channel uses the average
+        true range (ATR) or volatility, with breaks above or below the top
+        and bottom barriers signaling a continuation.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the Keltner Channels calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date"
+        length : PositiveInt, optional
+            The length of the Keltner Channels, by default 20
+        scalar : PositiveFloat, optional
+            The scalar to use for the Keltner Channels, by default 20
+        mamode : Literal["ema", "sma", "wma", "hma", "zlma"], optional
+            The moving average mode to use for the Keltner Channels, by default "ema"
+        offset : NonNegativeInt, optional
+            The offset to use for the Keltner Channels, by default 0
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The Keltner Channels data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> kc_data = obb.ta.kc(data=stock_data.results, length=20, scalar=20, ma_mode="ema", offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            length=length,
+            scalar=scalar,
+            mamode=mamode,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/kc",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def macd(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        fast: int = 12,
+        slow: int = 26,
+        signal: int = 9,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+           The Moving Average Convergence Divergence (MACD) is the difference
+           between two Exponential Moving Averages. The Signal line is an Exponential Moving
+           Average of the MACD.
+
+        The MACD signals trend changes and indicates the start
+           of new trend direction. High values indicate overbought conditions, low values
+           indicate oversold conditions. Divergence with the price indicates an end to the
+           current trend, especially if the MACD is at extreme high or low values. When the MACD
+           line crosses above the signal line a buy signal is generated. When the MACD crosses
+           below the signal line a sell signal is generated. To confirm the signal, the MACD
+           should be above zero for a buy, and below zero for a sell.
+
+           Parameters
+           ----------
+           data : List[Data]
+               List of data to be used for the calculation.
+           target : str
+               Target column name.
+           fast : int, optional
+               Number of periods for the fast EMA, by default 12.
+           slow : int, optional
+               Number of periods for the slow EMA, by default 26.
+           signal : int, optional
+               Number of periods for the signal EMA, by default 9.
+
+           Returns
+           -------
+           OBBject[List[Data]]
+               The calculated data.
+
+           Examples
+           --------
+           >>> from openbb import obb
+           >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+           >>> macd_data = obb.ta.macd(data=stock_data.results,target="close",fast=12,slow=26,signal=9)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            fast=fast,
+            slow=slow,
+            signal=signal,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/macd",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def obv(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+           The On Balance Volume (OBV) is a cumulative total of the up and
+           down volume. When the close is higher than the previous close, the volume is added
+           to the running total, and when the close is lower than the previous close, the volume
+           is subtracted from the running total.
+
+        To interpret the OBV, look for the OBV
+           to move with the price or precede price moves. If the price moves before the OBV,
+           then it is a non-confirmed move. A series of rising peaks, or falling troughs, in the
+           OBV indicates a strong trend. If the OBV is flat, then the market is not trending.
+
+           Parameters
+           ----------
+           data : List[Data]
+               List of data to apply the indicator to.
+           index : str, optional
+               Index column name, by default "date"
+           offset : int, optional
+               How many periods to offset the result, by default 0.
+
+           Returns
+           -------
+           OBBject[List[Data]]
+               List of data with the indicator applied.
+
+           Examples
+           --------
+           >>> from openbb import obb
+           >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+           >>> obv_data = obb.ta.obv(data=stock_data.results, offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/obv",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def rsi(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 14,
+        scalar: float = 100.0,
+        drift: int = 1,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        The Relative Strength Index (RSI) calculates a ratio of the
+        recent upward price movements to the absolute price movement. The RSI ranges
+        from 0 to 100. The RSI is interpreted as an overbought/oversold indicator when
+        the value is over 70/below 30. You can also look for divergence with price. If
+        the price is making new highs/lows, and the RSI is not, it indicates a reversal.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the RSI calculation.
+        target : str
+            Target column name.
+        index : str, optional
+            Index column name to use with `data`, by default "date"
+        length : int, optional
+            The length of the RSI, by default 14
+        scalar : float, optional
+            The scalar to use for the RSI, by default 100.0
+        drift : int, optional
+            The drift to use for the RSI, by default 1
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The RSI data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> rsi_data = obb.ta.rsi(data=stock_data.results, target="close", length=14, scalar=100.0, drift=1)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            scalar=scalar,
+            drift=drift,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/rsi",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def sma(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 50,
+        offset: int = 0,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        Moving Averages are used to smooth the data in an array to
+        help eliminate noise and identify trends. The Simple Moving Average is literally
+        the simplest form of a moving average. Each output value is the average of the
+        previous n values. In a Simple Moving Average, each value in the time period carries
+        equal weight, and values outside of the time period are not included in the average.
+        This makes it less responsive to recent changes in the data, which can be useful for
+        filtering out those changes.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        target : str
+            Target column name.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        length : int, optional
+            Number of periods to be used for the calculation, by default 50.
+        offset : int, optional
+            Offset from the current period, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> sma_data = obb.ta.sma(data=stock_data.results,target="close",length=50,offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            offset=offset,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/sma",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def stoch(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        fast_k_period: pydantic.types.NonNegativeInt = 14,
+        slow_d_period: pydantic.types.NonNegativeInt = 3,
+        slow_k_period: pydantic.types.NonNegativeInt = 3,
+    ) -> OBBject[List]:
+        """
+        The Stochastic Oscillator measures where the close is in relation
+        to the recent trading range. The values range from zero to 100. %D values over 75
+        indicate an overbought condition; values under 25 indicate an oversold condition.
+        When the Fast %D crosses above the Slow %D, it is a buy signal; when it crosses
+        below, it is a sell signal. The Raw %K is generally considered too erratic to use
+        for crossover signals.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the Stochastic Oscillator calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        fast_k_period : NonNegativeInt, optional
+            The fast %K period, by default 14.
+        slow_d_period : NonNegativeInt, optional
+            The slow %D period, by default 3.
+        slow_k_period : NonNegativeInt, optional
+            The slow %K period, by default 3.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The Stochastic Oscillator data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> stoch_data = obb.ta.stoch(data=stock_data.results, fast_k_period=14, slow_d_period=3, slow_k_period=3)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            fast_k_period=fast_k_period,
+            slow_d_period=slow_d_period,
+            slow_k_period=slow_k_period,
+        )
+
+        return self._command_runner.run(
+            "/ta/stoch",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def vwap(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        index: str = "date",
+        anchor: str = "D",
+        offset: int = 0,
+    ) -> OBBject[List]:
+        """
+        The Volume Weighted Average Price that measures the average typical price
+        by volume.  It is typically used with intraday charts to identify general direction.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        anchor : str, optional
+            Anchor period to use for the calculation, by default "D".
+            See Timeseries Offset Aliases below for additional options:
+            https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases
+        offset : int, optional
+            Offset from the current period, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> vwap_data = obb.ta.vwap(data=stock_data.results,anchor="D",offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            index=index,
+            anchor=anchor,
+            offset=offset,
+        )
+
+        return self._command_runner.run(
+            "/ta/vwap",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def wma(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 50,
+        offset: int = 0,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        A Weighted Moving Average puts more weight on recent data and less on past data.
+        This is done by multiplying each bar’s price by a weighting factor. Because of its
+        unique calculation, WMA will follow prices more closely than a corresponding Simple
+        Moving Average.
+
+        Parameters
+        ----------
+        data : List[Data]
+            The data to use for the calculation.
+        target : str
+            Target column name.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        length : int, optional
+            The length of the WMA, by default 50.
+        offset : int, optional
+            The offset of the WMA, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The WMA data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> wma_data = obb.ta.wma(data=stock_data.results, target="close", length=50, offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            offset=offset,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/wma",
+            **inputs,
+        )
+
+    @validate_arguments(config=dict(arbitrary_types_allowed=True))
+    def zlma(
+        self,
+        data: Union[List[openbb_provider.abstract.data.Data], pandas.DataFrame],
+        target: str = "close",
+        index: str = "date",
+        length: int = 50,
+        offset: int = 0,
+        chart: bool = False,
+    ) -> OBBject[List]:
+        """
+        The zero lag exponential moving average (ZLEMA) indicator
+        was created by John Ehlers and Ric Way. The idea is do a
+        regular exponential moving average (EMA) calculation but
+        on a de-lagged data instead of doing it on the regular data.
+        Data is de-lagged by removing the data from "lag" days ago
+        thus removing (or attempting to) the cumulative effect of
+        the moving average.
+
+        Parameters
+        ----------
+        data : List[Data]
+            List of data to be used for the calculation.
+        target : str
+            Target column name.
+        index : str, optional
+            Index column name to use with `data`, by default "date".
+        length : int, optional
+            Number of periods to be used for the calculation, by default 50.
+        offset : int, optional
+            Offset to be used for the calculation, by default 0.
+
+        Returns
+        -------
+        OBBject[List[Data]]
+            The calculated data.
+
+        Examples
+        --------
+        >>> from openbb import obb
+        >>> stock_data = obb.stocks.load(symbol="TSLA", start_date="2023-01-01", provider="fmp")
+        >>> zlma_data = obb.ta.zlma(data=stock_data.results, target="close", length=50, offset=0)
+        """  # noqa: E501
+
+        inputs = filter_inputs(
+            data=data,
+            target=target,
+            index=index,
+            length=length,
+            offset=offset,
+            chart=chart,
+        )
+
+        return self._command_runner.run(
+            "/ta/zlma",
+            **inputs,
+        )
diff --git a/openbb_sdk/poetry.lock b/openbb_sdk/poetry.lock
index 1b1f1ae724d..b13e9e015ce 100644
--- a/openbb_sdk/poetry.lock
+++ b/openbb_sdk/poetry.lock
@@ -306,7 +306,7 @@ uvloop = ["uvloop (>=0.15.2)"]
 name = "cattrs"
 version = "23.1.2"
 description = "Composable complex class support for attrs and dataclasses."
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "cattrs-23.1.2-py3-none-any.whl", hash = "sha256:b2bb14311ac17bed0d58785e5a60f022e5431aca3932e3fc5cc8ed8639de50a4"},
@@ -727,6 +727,17 @@ zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
 
+[[package]]
+name = "inflection"
+version = "0.5.1"
+description = "A port of Ruby on Rails inflector to Python"
+optional = true
+python-versions = ">=3.5"
+files = [
+    {file = "inflection-0.5.1-py2.py3-none-any.whl", hash = "sha256:f38b2b640938a4f35ade69ac3d053042959b62a0f1076a5bbaa1b9526605a8a2"},
+    {file = "inflection-0.5.1.tar.gz", hash = "sha256:1a29730d366e996aaacffb2f1f1cb9593dc38e2ddd30c91250c6dde09ea9b417"},
+]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -925,6 +936,17 @@ files = [
     {file = "monotonic-1.6.tar.gz", hash = "sha256:3a55207bcfed53ddd5c5bae174524062935efed17792e9de2ad0205ce9ad63f7"},
 ]
 
+[[package]]
+name = "more-itertools"
+version = "10.1.0"
+description = "More routines for operating on iterables, beyond itertools"
+optional = true
+python-versions = ">=3.8"
+files = [
+    {file = "more-itertools-10.1.0.tar.gz", hash = "sha256:626c369fa0eb37bac0291bce8259b332fd59ac792fa5497b59837309cd5b114a"},
+    {file = "more_itertools-10.1.0-py3-none-any.whl", hash = "sha256:64e0735fcfdc6f3464ea133afe8ea4483b1c5fe3a3d69852e6503b43a0b222e6"},
+]
+
 [[package]]
 name = "multidict"
 version = "6.0.4"
@@ -1088,6 +1110,22 @@ files = [
     {file = "numpy-1.24.4.tar.gz", hash = "sha256:80f5e3a4e498641401868df4208b74581206afbee7cf7b8329daae82676d9463"},
 ]
 
+[[package]]
+name = "openbb-alpha-vantage"
+version = "0.1.0"
+description = ""
+optional = true
+python-versions = "^3.8"
+files = []
+develop = false
+
+[package.dependencies]
+openbb-core = {path = "../../sdk/core"}
+
+[package.source]
+type = "directory"
+url = "providers/alpha_vantage"
+
 [[package]]
 name = "openbb-benzinga"
 version = "0.1.0"
@@ -1287,6 +1325,23 @@ openbb-core = {path = "../../sdk/core"}
 type = "directory"
 url = "extensions/futures"
 
+[[package]]
+name = "openbb-intrinio"
+version = "0.1.0"
+description = "Intrinio extension for OpenBB"
+optional = false
+python-versions = "^3.8"
+files = []
+develop = false
+
+[package.dependencies]
+openbb-core = {path = "../../sdk/core"}
+requests-cache = "^1.1.0"
+
+[package.source]
+type = "directory"
+url = "providers/intrinio"
+
 [[package]]
 name = "openbb-news"
 version = "0.1.0"
@@ -1357,6 +1412,23 @@ statsmodels = "^0.14.0"
 type = "directory"
 url = "extensions/qa"
 
+[[package]]
+name = "openbb-quandl"
+version = "0.1.0"
+description = ""
+optional = true
+python-versions = "^3.8"
+files = []
+develop = false
+
+[package.dependencies]
+openbb-core = {path = "../../sdk/core"}
+quandl = ">=3.7.0"
+
+[package.source]
+type = "directory"
+url = "providers/quandl"
+
 [[package]]
 name = "openbb-stocks"
 version = "0.1.0"
@@ -1922,6 +1994,26 @@ setproctitle = "*"
 [package.extras]
 dev = ["auditwheel", "wheel"]
 
+[[package]]
+name = "quandl"
+version = "3.7.0"
+description = "Package for quandl API access"
+optional = true
+python-versions = ">= 3.6"
+files = [
+    {file = "Quandl-3.7.0-py2.py3-none-any.whl", hash = "sha256:0e3e5dc60fd057c73c67380b1b0f2e3dc0e4c500fb5e6e146ac3a3c0d992cd1d"},
+    {file = "Quandl-3.7.0.tar.gz", hash = "sha256:6e0b82fbc7861610b3577c5397277c4220e065eee0fed4e46cd6b6021655b64c"},
+]
+
+[package.dependencies]
+inflection = ">=0.3.1"
+more-itertools = "*"
+numpy = ">=1.8"
+pandas = ">=0.14"
+python-dateutil = "*"
+requests = ">=2.7.0"
+six = "*"
+
 [[package]]
 name = "referencing"
 version = "0.30.2"
@@ -1981,7 +2073,7 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-cache"
 version = "1.1.0"
 description = "A persistent cache for python requests"
-optional = true
+optional = false
 python-versions = ">=3.7,<4.0"
 files = [
     {file = "requests_cache-1.1.0-py3-none-any.whl", hash = "sha256:178282bce704b912c59e7f88f367c42bddd6cde6bf511b2a3e3cfb7e5332a92a"},
@@ -2535,7 +2627,7 @@ files = [
 name = "url-normalize"
 version = "1.4.3"
 description = "URL normalization for Python"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
     {file = "url-normalize-1.4.3.tar.gz", hash = "sha256:d23d3a070ac52a67b83a1c59a0e68f8608d1cd538783b401bc9de2c0fac999b2"},
@@ -2805,15 +2897,17 @@ docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.link
 testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
 
 [extras]
-all = ["openbb-cboe", "openbb-charting", "openbb-futures", "openbb-qa", "openbb-ta", "openbb-yfinance"]
+all = ["openbb-alpha-vantage", "openbb-cboe", "openbb-charting", "openbb-futures", "openbb-qa", "openbb-quandl", "openbb-ta", "openbb-yfinance"]
+alpha-vantage = ["openbb-alpha-vantage"]
 cboe = ["openbb-cboe"]
 charting = ["openbb-charting"]
 futures = ["openbb-futures"]
 qa = ["openbb-qa"]
+quandl = ["openbb-quandl"]
 ta = ["openbb-ta"]
 yfinance = ["openbb-yfinance"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8,<3.12"
-content-hash = "e3a2f27c7308848ee2bc8fc6130ec2a7bc144803c53c9bca3b25565aeefb7580"
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diff --git a/openbb_sdk/providers/alpha_vantage/README.md b/openbb_sdk/providers/alpha_vantage/README.md
new file mode 100644
index 00000000000..6a6d3f6eda4
--- /dev/null
+++ b/openbb_sdk/providers/alpha_vantage/README.md
@@ -0,0 +1,11 @@
+# OpenBB Alpha Vantage Provider
+
+This extension integrates the Alpha Vantage data provider into the OpenBB SDK.
+
+## Installation
+
+To install the extension, run the following command in this folder:
+
+```bash
+pip install .
+```
diff --git a/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/__init__.py b/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/__init__.py
new file mode 100644
index 00000000000..1fd690f1e32
--- /dev/null
+++ b/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/__init__.py
@@ -0,0 +1,20 @@
+"""Alpha Vantage Provider module."""
+from openbb_provider.abstract.provider import Provider
+
+from openbb_alpha_vantage.models.stock_historical import AVStockHistoricalFetcher
+
+alpha_vantage_provider = Provider(
+    name="alpha_vantage",
+    website="https://www.alphavantage.co/documentation/",
+    description="""Alpha Vantage provides realtime and historical
+    financial market data through a set of powerful and developer-friendly data APIs
+    and spreadsheets. From traditional asset classes (e.g., stocks, ETFs, mutual funds)
+    to economic indicators, from foreign exchange rates to commodities,
+    from fundamental data to technical indicators, Alpha Vantage
+    is your one-stop-shop for enterprise-grade global market data delivered through
+    cloud-based APIs, Excel, and Google Sheets. """,
+    required_credentials=["api_key"],
+    fetcher_dict={
+        "StockHistorical": AVStockHistoricalFetcher,
+    },
+)
diff --git a/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/models/__init__.py b/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/models/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/models/stock_historical.py b/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/models/stock_historical.py
new file mode 100644
index 00000000000..fbbb402e14e
--- /dev/null
+++ b/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/models/stock_historical.py
@@ -0,0 +1,247 @@
+"""Alpha Vantage Stock End of Day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional, get_args
+
+import pandas as pd
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_historical import (
+    StockHistoricalData,
+    StockHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, NonNegativeFloat, PositiveFloat, root_validator, validator
+
+
+class AVStockHistoricalQueryParams(StockHistoricalQueryParams):
+    """Alpha Vantage Stock End of Day Query.
+
+    Source: https://www.alphavantage.co/documentation/
+    """
+
+    _function: Literal[
+        "TIME_SERIES_INTRADAY",
+        "TIME_SERIES_DAILY",
+        "TIME_SERIES_WEEKLY",
+        "TIME_SERIES_MONTHLY",
+        "TIME_SERIES_DAILY_ADJUSTED",
+        "TIME_SERIES_WEEKLY_ADJUSTED",
+        "TIME_SERIES_MONTHLY_ADJUSTED",
+    ] = Field(
+        description="The time series of your choice. ",
+        default="TIME_SERIES_DAILY",
+    )
+    period: Literal["intraday", "daily", "weekly", "monthly"] = Field(
+        default="daily", description=QUERY_DESCRIPTIONS.get("period", "")
+    )
+    interval: Optional[Literal["1min", "5min", "15min", "30min", "60min"]] = Field(
+        description="The interval between two consecutive data points in the time series.",
+        default="60min",
+        available_on_functions=["TIME_SERIES_INTRADAY"],
+        required_on_functions=["TIME_SERIES_INTRADAY"],
+    )
+    adjusted: Optional[bool] = Field(
+        description="Output time series is adjusted by historical split and dividend events.",
+        default=True,
+        available_on_functions=["TIME_SERIES_INTRADAY"],
+    )
+    extended_hours: Optional[bool] = Field(
+        description="Extended trading hours during pre-market and after-hours.",
+        default=False,
+        available_on_functions=["TIME_SERIES_INTRADAY"],
+    )
+    month: Optional[str] = Field(
+        description="Query a specific month in history (in YYYY-MM format).",
+        default=None,
+        available_on_functions=["TIME_SERIES_INTRADAY"],
+    )
+    outputsize: Optional[Literal["compact", "full"]] = Field(
+        description="Compact returns only the latest 100 data points in the intraday "
+        "time series; full returns trailing 30 days of the most recent intraday data "
+        "if the month parameter (see above) is not specified, or the full intraday "
+        "data for a specific month in history if the month parameter is specified.",
+        default="full",
+        available_on_functions=[
+            "TIME_SERIES_INTRADAY",
+            "TIME_SERIES_DAILY",
+            "TIME_SERIES_DAILY_ADJUSTED",
+        ],
+    )
+
+    @root_validator
+    def setup_function(cls, values):  # pylint: disable=E0213
+        """Set the function based on the period."""
+
+        functions_based_on_period = {
+            "intraday": "TIME_SERIES_INTRADAY",
+            "daily": "TIME_SERIES_DAILY",
+            "weekly": "TIME_SERIES_WEEKLY",
+            "monthly": "TIME_SERIES_MONTHLY",
+        }
+        values["_function"] = functions_based_on_period[values["period"]]
+        return values
+
+    @root_validator
+    def adjusted_function_validate(cls, values):  # pylint: disable=E0213
+        """
+        Validate that the function is adjusted if the `adjusted` parameter is set to True.
+        """
+
+        function = values["_function"]
+        adjusted = values.get("adjusted", None)
+
+        if function != "TIME_SERIES_INTRADAY":
+            values["_function"] = function if not adjusted else f"{function}_ADJUSTED"
+
+        return values
+
+    @root_validator
+    def on_functions_validate(cls, values):  # pylint: disable=E0213
+        """
+        Validate that the functions used on custom extra Field attributes
+        `available_on_functions` and `required_on_functions` are valid functions.
+        """
+        custom_attributes = ["available_on_functions", "required_on_functions"]
+
+        fields = cls.__fields__
+        available_functions = get_args(cls.__annotations__["_function"])
+
+        if values["_function"] not in available_functions:
+            raise ValueError(
+                f"Function {values['_function']} must be on of the following: {available_functions}"
+            )
+
+        def validate_functions(functions: List[str]):
+            for f in functions:
+                if f not in available_functions:
+                    raise ValueError(
+                        f"Function {f} must be on of the following: {available_functions}"
+                    )
+
+        for field in fields:
+            for attr in custom_attributes:
+                if functions := fields[field].field_info.extra.get(attr, None):
+                    validate_functions(functions)
+
+        return values
+
+    @root_validator
+    def on_functions_criteria_validate(cls, values):  # pylint: disable=E0213
+        """
+        Validate that the fields are set to None if the function is not available
+        and that the required fields are not None if the function is required.
+        """
+
+        fields = cls.__fields__
+        function = values["_function"]
+
+        for field in fields:
+            if (
+                available_on_functions := fields[field].field_info.extra.get(
+                    "available_on_functions", None
+                )
+            ) and function not in available_on_functions:
+                values[field] = None
+            if (
+                (
+                    required_on_functions := fields[field].field_info.extra.get(
+                        "required_on_functions", None
+                    )
+                )
+                and function in required_on_functions
+                and values[field] is None
+            ):
+                raise ValueError(f"Field {field} is required on function {function}")
+
+        return values
+
+    @validator("month")
+    def month_validate(cls, v):  # pylint: disable=E0213
+        """Validate month, check if the month is in YYYY-MM format."""
+        if v is not None:
+            try:
+                datetime.strptime(v, "%Y-%m")
+            except ValueError as e:
+                raise e
+        return v
+
+
+class AVStockHistoricalData(StockHistoricalData):
+    """Alpha Vantage Stock End of Day Data."""
+
+    class Config:
+        """Pydantic alias config using fields dict."""
+
+        fields = {"date": "timestamp", "adj_close": "adjusted_close"}
+
+    adjusted_close: PositiveFloat = Field(
+        description=DATA_DESCRIPTIONS.get("adj_close", "")
+    )
+    dividend_amount: NonNegativeFloat = Field(
+        description="Dividend amount paid for the corresponding date.",
+    )
+    split_coefficient: NonNegativeFloat = Field(
+        description="Split coefficient for the corresponding date.",
+    )
+
+
+class AVStockHistoricalFetcher(
+    Fetcher[
+        AVStockHistoricalQueryParams,
+        List[AVStockHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Alpha Vantage endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> AVStockHistoricalQueryParams:
+        """Transform the query."""
+
+        transformed_params = params
+
+        now = datetime.now().date()
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+
+        return AVStockHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: AVStockHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the Alpha Vantage endpoint."""
+
+        api_key = credentials.get("alpha_vantage_api_key") if credentials else ""
+
+        query_dict = query.dict()
+        query_dict["function"] = query_dict.pop("_function")
+
+        query_str = get_querystring(query_dict, ["start_date", "end_date"])
+
+        url = f"https://www.alphavantage.co/query?{query_str}&datatype=csv&apikey={api_key}"
+
+        data = pd.read_csv(url)
+        data["timestamp"] = pd.to_datetime(data["timestamp"])
+
+        data = data[
+            (data["timestamp"] >= pd.to_datetime(query.start_date))
+            & (data["timestamp"] <= pd.to_datetime(query.end_date))
+        ]
+
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[AVStockHistoricalData]:
+        """Transform the data to the standard format."""
+
+        return [AVStockHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/utils/__init__.py b/openbb_sdk/providers/alpha_vantage/openbb_alpha_vantage/utils/__init__.py
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new file mode 100644
index 00000000000..4ceb7c5e95f
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+]
+
+[[package]]
+name = "zipp"
+version = "3.16.2"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
+    {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.8"
+content-hash = "ed5c1001c4f47bae1cfde8d8509294643e3b3ea101a8482c3f0248085360bb18"
diff --git a/openbb_sdk/providers/alpha_vantage/pyproject.toml b/openbb_sdk/providers/alpha_vantage/pyproject.toml
new file mode 100644
index 00000000000..64ca1cdc6f0
--- /dev/null
+++ b/openbb_sdk/providers/alpha_vantage/pyproject.toml
@@ -0,0 +1,18 @@
+[tool.poetry]
+name = "openbb-alpha-vantage"
+version = "0.1.0"
+description = ""
+authors = ["OpenBB Team <hello@openbb.co>"]
+readme = "README.md"
+packages = [{ include = "openbb_alpha_vantage" }]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+openbb-core = { path = "../../sdk/core" }
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.plugins."openbb_provider_extension"]
+alpha_vantage = "openbb_alpha_vantage:alpha_vantage_provider"
diff --git a/openbb_sdk/providers/alpha_vantage/tests/.gitkeep b/openbb_sdk/providers/alpha_vantage/tests/.gitkeep
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/__init__.py b/openbb_sdk/providers/cboe/openbb_cboe/__init__.py
index ad624d02a84..7f6c94eb990 100644
--- a/openbb_sdk/providers/cboe/openbb_cboe/__init__.py
+++ b/openbb_sdk/providers/cboe/openbb_cboe/__init__.py
@@ -3,8 +3,21 @@
 
 from openbb_provider.abstract.provider import Provider
 
+from openbb_cboe.models.available_indices import CboeAvailableIndicesFetcher
+from openbb_cboe.models.european_index_constituents import (
+    CboeEuropeanIndexConstituentsFetcher,
+)
+from openbb_cboe.models.european_index_historical import (
+    CboeEuropeanIndexHistoricalFetcher,
+)
+from openbb_cboe.models.futures_curve import CboeFuturesCurveFetcher
+from openbb_cboe.models.index_search import CboeIndexSearchFetcher
+from openbb_cboe.models.index_snapshots import CboeIndexSnapshotsFetcher
+from openbb_cboe.models.major_indices_historical import (
+    CboeMajorIndicesHistoricalFetcher,
+)
 from openbb_cboe.models.options_chains import CboeOptionsChainsFetcher
-from openbb_cboe.models.stock_eod import CboeStockEODFetcher
+from openbb_cboe.models.stock_historical import CboeStockHistoricalFetcher
 from openbb_cboe.models.stock_info import CboeStockInfoFetcher
 from openbb_cboe.models.stock_search import CboeStockSearchFetcher
 
@@ -18,7 +31,14 @@ cboe_provider = Provider(
     fetcher_dict={
         "StockSearch": CboeStockSearchFetcher,
         "OptionsChains": CboeOptionsChainsFetcher,
-        "StockEOD": CboeStockEODFetcher,
+        "StockHistorical": CboeStockHistoricalFetcher,
         "StockInfo": CboeStockInfoFetcher,
+        "FuturesCurve": CboeFuturesCurveFetcher,
+        "AvailableIndices": CboeAvailableIndicesFetcher,
+        "EuropeanIndexConstituents": CboeEuropeanIndexConstituentsFetcher,
+        "EuropeanIndexHistorical": CboeEuropeanIndexHistoricalFetcher,
+        "MajorIndicesHistorical": CboeMajorIndicesHistoricalFetcher,
+        "IndexSearch": CboeIndexSearchFetcher,
+        "IndexSnapshots": CboeIndexSnapshotsFetcher,
     },
 )
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/available_indices.py b/openbb_sdk/providers/cboe/openbb_cboe/models/available_indices.py
new file mode 100644
index 00000000000..b401279577d
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/available_indices.py
@@ -0,0 +1,106 @@
+"""Available Indices fetcher for CBOE"""
+
+from datetime import time
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.available_indices import (
+    AvailableIndicesData,
+    AvailableIndicesQueryParams,
+)
+from pydantic import Field
+
+from openbb_cboe.utils.helpers import Europe, get_cboe_index_directory
+
+
+class CboeAvailableIndicesQueryParams(AvailableIndicesQueryParams):
+    """CBOE Available Indices query.
+
+    Source: https://www.cboe.com/europe/indices/
+    """
+
+    europe: bool = Field(
+        description="Filter for European indices. False for US indices.", default=False
+    )
+
+
+class CboeAvailableIndicesData(AvailableIndicesData):
+    """CBOE Available Indices data.
+
+    Source: https://www.cboe.com/europe/indices/
+    """
+
+    isin: Optional[str] = Field(
+        description="ISIN code for the index. Valid only for European indices."
+    )
+
+    region: Optional[str] = Field(
+        description="Region for the index. Valid only for European indices"
+    )
+
+    symbol: Optional[str] = Field(description="Symbol for the index.")
+
+    description: Optional[str] = Field(
+        description="Description for the index. Valid only for US indices."
+    )
+
+    data_delay: Optional[int] = Field(
+        description="Data delay for the index. Valid only for US indices."
+    )
+
+    open_time: Optional[time] = Field(
+        description="Opening time for the index. Valid only for US indices."
+    )
+
+    close_time: Optional[time] = Field(
+        description="Closing time for the index. Valid only for US indices."
+    )
+
+    time_zone: Optional[str] = Field(
+        description="Time zone for the index. Valid only for US indices."
+    )
+
+    tick_days: Optional[str] = Field(
+        description="The trading days for the index. Valid only for US indices."
+    )
+
+    tick_frequency: Optional[str] = Field(
+        description="The frequency of the index ticks. Valid only for US indices."
+    )
+
+    tick_period: Optional[str] = Field(
+        description="The period of the index ticks. Valid only for US indices."
+    )
+
+
+class CboeAvailableIndicesFetcher(
+    Fetcher[
+        CboeAvailableIndicesQueryParams,
+        CboeAvailableIndicesData,
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> CboeAvailableIndicesQueryParams:
+        """Transform the query params."""
+
+        return CboeAvailableIndicesQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeAvailableIndicesQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        if query.europe is True:
+            return Europe.list_indices()
+        return get_cboe_index_directory().sort_index().reset_index().to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[CboeAvailableIndicesData]:
+        """Transform the data to the standard format"""
+
+        return [CboeAvailableIndicesData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/european_index_constituents.py b/openbb_sdk/providers/cboe/openbb_cboe/models/european_index_constituents.py
new file mode 100644
index 00000000000..67c876c4c0b
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/european_index_constituents.py
@@ -0,0 +1,113 @@
+"""CBOE European Index Constituents fetcher."""
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.european_index_constituents import (
+    EuropeanIndexConstituentsData,
+    EuropeanIndexConstituentsQueryParams,
+)
+from openbb_provider.utils.helpers import make_request
+from pydantic import Field, validator
+
+from openbb_cboe.utils.helpers import EUR_INDEX_CONSTITUENTS_COLUMNS, Europe
+
+
+class CboeEuropeanIndexConstituentsQueryParams(EuropeanIndexConstituentsQueryParams):
+    """CBOE Stock end of day query.
+
+    Source: https://www.cboe.com/
+
+    Gets the current price data for all constituents of the CBOE European Index.
+    """
+
+
+class CboeEuropeanIndexConstituentsData(EuropeanIndexConstituentsData):
+    """CBOE European Index Constituents Data.
+
+    Current trading day price data for all constituents of the CBOE European Index.
+    """
+
+    prev_close: Optional[float] = Field(description="Previous closing  price.")
+    change: Optional[float] = Field(description="Change in price.")
+    change_percent: Optional[float] = Field(
+        description="Change in price as a percentage."
+    )
+    tick: Optional[str] = Field(
+        description="Whether the last sale was an up or down tick."
+    )
+    last_trade_timestamp: Optional[datetime] = Field(
+        description="Last trade timestamp for the symbol."
+    )
+    exchange_id: Optional[int] = Field(description="The Exchange ID number.")
+    seqno: Optional[int] = Field(
+        description="Sequence number of the last trade on the tape."
+    )
+    asset_type: Optional[str] = Field(description="Type of asset.", alias="type")
+
+    @validator("last_trade_timestamp", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the datetime object from the date string"""
+
+        return datetime.strftime(v, "%Y-%m-%d %H:%M:%S")
+
+
+class CboeEuropeanIndexConstituentsFetcher(
+    Fetcher[
+        CboeEuropeanIndexConstituentsQueryParams,
+        List[CboeEuropeanIndexConstituentsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(
+        params: Dict[str, Any]
+    ) -> CboeEuropeanIndexConstituentsQueryParams:
+        """Transform the query."""
+
+        return CboeEuropeanIndexConstituentsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeEuropeanIndexConstituentsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        SYMBOLS = pd.DataFrame(Europe.list_indices())["symbol"].to_list()
+        query.symbol = query.symbol.upper()
+
+        if query.symbol not in SYMBOLS:
+            raise RuntimeError(
+                f"The symbol, {query.symbol},"
+                "was not found in the CBOE European Index directory. "
+                "Use `available_indices(europe=True)` to see the full list of indices."
+            )
+        url = f"https://cdn.cboe.com/api/global/european_indices/constituent_quotes/{query.symbol}.json"
+
+        r = make_request(url)
+        if r.status_code != 200:
+            raise RuntimeError(r.status_code)
+
+        r_json = r.json()
+
+        data = (
+            pd.DataFrame.from_records(r_json["data"])[
+                list(EUR_INDEX_CONSTITUENTS_COLUMNS.keys())
+            ]
+            .rename(columns=EUR_INDEX_CONSTITUENTS_COLUMNS)
+            .round(2)
+        )
+        data["last_trade_timestamp"] = pd.to_datetime(data["last_trade_timestamp"])
+
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[CboeEuropeanIndexConstituentsData]:
+        """Transform the data to the standard format"""
+
+        return [CboeEuropeanIndexConstituentsData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/european_index_historical.py b/openbb_sdk/providers/cboe/openbb_cboe/models/european_index_historical.py
new file mode 100644
index 00000000000..e289f000561
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/european_index_historical.py
@@ -0,0 +1,134 @@
+"""European Indices End of Day fetcher for CBOE."""
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.european_index_historical import (
+    EuropeanIndexHistoricalData,
+    EuropeanIndexHistoricalQueryParams,
+)
+from openbb_provider.utils.helpers import make_request
+from pydantic import Field, validator
+
+from openbb_cboe.utils.helpers import Europe
+
+
+class CboeEuropeanIndexHistoricalQueryParams(EuropeanIndexHistoricalQueryParams):
+    """CBOE European Indices End of Day query.
+
+    Source: https://www.cboe.com/europe/indices/
+    """
+
+    interval: Optional[Literal["1d", "1m"]] = Field(
+        description="Use interval, 1m, for intraday prices during the most recent trading period.",
+        default="1d",
+    )
+
+
+class CboeEuropeanIndexHistoricalData(EuropeanIndexHistoricalData):
+    """CBOE Stocks End of Day Data."""
+
+    open: Optional[float] = Field(
+        description="Opening price for the interval. Only valid when interval is 1m."
+    )
+    high: Optional[float] = Field(
+        description="High price for the interval. Only valid when interval is 1m."
+    )
+    low: Optional[float] = Field(
+        description="Low price for the interval. Only valid when interval is 1m."
+    )
+    utc_datetime: Optional[datetime] = Field(
+        description="UTC datetime. Only valid when interval is 1m."
+    )
+
+    @validator("close", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the datetime object from the date string"""
+        return float(v)
+
+
+class CboeEuropeanIndexHistoricalFetcher(
+    Fetcher[
+        CboeEuropeanIndexHistoricalQueryParams,
+        List[CboeEuropeanIndexHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(
+        params: Dict[str, Any]
+    ) -> CboeEuropeanIndexHistoricalQueryParams:
+        """Transform the query."""
+
+        return CboeEuropeanIndexHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeEuropeanIndexHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        data = pd.DataFrame()
+        query.symbol = query.symbol.upper()
+        SYMBOLS = pd.DataFrame(Europe.list_indices())["symbol"].to_list()
+
+        if query.symbol not in SYMBOLS:
+            raise RuntimeError(
+                f"The symbol, {query.symbol},"
+                "was not found in the CBOE European Index directory. "
+                "Use `available_indices(europe=True)` to see the full list of indices."
+            )
+        if query.interval == "1d":
+            url = f"https://cdn.cboe.com/api/global/european_indices/index_history/{query.symbol}.json"
+
+            r = make_request(url)
+            if r.status_code != 200:
+                raise RuntimeError(r.status_code)
+
+            r_json = r.json()
+
+            data = pd.DataFrame.from_records(r_json["data"]).set_index("date")
+
+            data.index = pd.to_datetime(data.index, format="%Y-%m-%d")
+
+            if query.start_date is not None:
+                query.end_date = (
+                    query.end_date if query.end_date else datetime.now().date()
+                )
+
+                data = data[
+                    (data.index >= pd.to_datetime(query.start_date, format="%Y-%m-%d"))
+                    & (data.index <= pd.to_datetime(query.end_date, format="%Y-%m-%d"))
+                ]
+            data.index = data.index.astype(str)
+            data = data.reset_index()
+
+        if query.interval == "1m":
+            url = f"https://cdn.cboe.com/api/global/european_indices/intraday_chart_data/{query.symbol}.json"
+
+            r = make_request(url)
+            if r.status_code != 200:
+                raise RuntimeError(r.status_code)
+
+            r_json = r.json()["data"]
+
+            data = pd.DataFrame.from_records(pd.DataFrame(r_json)["price"])
+            data["date"] = pd.DataFrame(r_json)["datetime"]
+            data["utc_datetime"] = pd.to_datetime(pd.DataFrame(r_json)["utc_datetime"])
+
+            data = data[["utc_datetime", "date", "open", "high", "low", "close"]].round(
+                2
+            )
+
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[CboeEuropeanIndexHistoricalData]:
+        """Transform the data to the standard format"""
+
+        return [CboeEuropeanIndexHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/futures_curve.py b/openbb_sdk/providers/cboe/openbb_cboe/models/futures_curve.py
new file mode 100644
index 00000000000..dcbecf4e67d
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/futures_curve.py
@@ -0,0 +1,70 @@
+"""CBOE Futures Curve Fetcher."""
+
+# IMPORT STANDARD
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.futures_curve import (
+    FuturesCurveData,
+    FuturesCurveQueryParams,
+)
+from pydantic import Field
+
+from openbb_cboe.utils.helpers import get_settlement_prices
+
+
+class CboeFuturesCurveQueryParams(FuturesCurveQueryParams):
+    """CBOE Futures Curve Query.
+
+    Source: https://www.cboe.com/
+    """
+
+
+class CboeFuturesCurveData(FuturesCurveData):
+    """CBOE Futures Curve Data."""
+
+    symbol: str = Field(description="The trading symbol for the tenor of future.")
+
+
+class CboeFuturesCurveFetcher(
+    Fetcher[
+        CboeFuturesCurveQueryParams,
+        List[CboeFuturesCurveData],
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> CboeFuturesCurveQueryParams:
+        return CboeFuturesCurveQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeFuturesCurveQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the CBOE endpoint."""
+
+        query.symbol = query.symbol.upper()
+        FUTURES = get_settlement_prices(settlement_date=query.date)
+        if len(FUTURES) == 0:
+            return pd.DataFrame()
+
+        if query.symbol not in FUTURES["product"].unique().tolist():
+            raise RuntimeError(
+                "The symbol, "
+                f"{query.symbol}"
+                ", is not valid.  Chose from: "
+                f"{FUTURES['product'].unique().tolist()}"
+            )
+
+        data = get_settlement_prices(settlement_date=query.date)
+        data = data[data["product"] == query.symbol]
+
+        return data[["expiration", "symbol", "price"]].to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[CboeFuturesCurveData]:
+        return [CboeFuturesCurveData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/index_search.py b/openbb_sdk/providers/cboe/openbb_cboe/models/index_search.py
new file mode 100644
index 00000000000..bf3545b7720
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/index_search.py
@@ -0,0 +1,99 @@
+"""CBOE Index Search fetcher."""
+
+from datetime import time
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.index_search import (
+    IndexSearchData,
+    IndexSearchQueryParams,
+)
+from pydantic import Field
+
+from openbb_cboe.utils.helpers import Europe, get_cboe_index_directory
+
+
+class CboeIndexSearchQueryParams(IndexSearchQueryParams):
+    """CBOE Index Search query.  Search the CBOE company directory by name or ticker.
+
+    Source: https://www.cboe.com/
+    """
+
+    europe: bool = Field(
+        description="Filter for European indices. False for US indices.", default=False
+    )
+
+
+class CboeIndexSearchData(IndexSearchData):
+    """CBOE Company Search Data."""
+
+    isin: Optional[str] = Field(
+        description="ISIN code for the index. Valid only for European indices."
+    )
+    region: Optional[str] = Field(
+        description="Region for the index. Valid only for European indices"
+    )
+    description: Optional[str] = Field(description="Description for the index.")
+    data_delay: Optional[int] = Field(
+        description="Data delay for the index. Valid only for US indices."
+    )
+    currency: Optional[str] = Field(description="Currency for the index.")
+    time_zone: Optional[str] = Field(
+        description="Time zone for the index. Valid only for US indices."
+    )
+    open_time: Optional[time] = Field(
+        description="Opening time for the index. Valid only for US indices."
+    )
+    close_time: Optional[time] = Field(
+        description="Closing time for the index. Valid only for US indices."
+    )
+    tick_days: Optional[str] = Field(
+        description="The trading days for the index. Valid only for US indices."
+    )
+    tick_frequency: Optional[str] = Field(
+        description="Tick frequency for the index. Valid only for US indices."
+    )
+    tick_period: Optional[str] = Field(
+        description="Tick period for the index. Valid only for US indices."
+    )
+
+
+class CboeIndexSearchFetcher(
+    Fetcher[
+        CboeIndexSearchQueryParams,
+        List[CboeIndexSearchData],
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> CboeIndexSearchQueryParams:
+        """Transform the query"""
+
+        return CboeIndexSearchQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeIndexSearchQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        symbols = pd.DataFrame()
+        if query.europe is True:
+            symbols = pd.DataFrame(Europe.list_indices())
+        if query.europe is False:
+            symbols = get_cboe_index_directory().reset_index()
+
+        target = "name" if not query.symbol else "symbol"
+        idx = symbols[target].str.contains(query.query, case=False)
+        result = symbols[idx]
+
+        return result.to_dict("records")
+
+    @staticmethod
+    def transform_data(data: dict) -> List[CboeIndexSearchData]:
+        """Transform the data to the standard format"""
+        return [CboeIndexSearchData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/index_snapshots.py b/openbb_sdk/providers/cboe/openbb_cboe/models/index_snapshots.py
new file mode 100644
index 00000000000..defd3f13f55
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/index_snapshots.py
@@ -0,0 +1,136 @@
+"""CBOE Index Snapshots fetcher."""
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.index_snapshots import (
+    IndexSnapshotsData,
+    IndexSnapshotsQueryParams,
+)
+from openbb_provider.utils.helpers import make_request
+from pydantic import Field
+
+from openbb_cboe.utils.helpers import (
+    EUR_INDEX_COLUMNS,
+    US_INDEX_COLUMNS,
+    Europe,
+    get_cboe_directory,
+    get_cboe_index_directory,
+)
+
+
+class CboeIndexSnapshotsQueryParams(IndexSnapshotsQueryParams):
+    """CBOE Index Snapshots query.  Returns quotes for all indices by region.
+
+    Source: https://www.cboe.com/
+    """
+
+
+class CboeIndexSnapshotsData(IndexSnapshotsData):
+    """CBOE Company Search Data."""
+
+    isin: Optional[str] = Field(
+        description="ISIN code for the index. Valid only for European indices."
+    )
+    last_trade_timestamp: Optional[datetime] = Field(
+        description="Last trade timestamp for the index."
+    )
+
+
+class CboeIndexSnapshotsFetcher(
+    Fetcher[
+        CboeIndexSnapshotsQueryParams,
+        List[CboeIndexSnapshotsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> CboeIndexSnapshotsQueryParams:
+        """Transform the query"""
+
+        return CboeIndexSnapshotsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeIndexSnapshotsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        data = pd.DataFrame()
+
+        if query.region == "US":
+            r = make_request(
+                "https://cdn.cboe.com/api/global/delayed_quotes/quotes/all_us_indices.json"
+            )
+
+            if r.status_code != 200:
+                raise RuntimeError(r.status_code)
+
+            INDEXES = pd.concat(
+                [get_cboe_index_directory(), get_cboe_directory()], axis=0
+            )
+            data = pd.DataFrame.from_records(r.json()["data"])
+
+            data.rename(columns=US_INDEX_COLUMNS, inplace=True)
+            data["symbol"] = data["symbol"].str.replace("^", "")
+            data["name"] = ""
+            data = data.set_index("symbol")
+            for i in data.index:
+                if i in INDEXES.index:
+                    data.at[i, "name"] = INDEXES.at[i, "name"]
+
+            data["name"] = data["name"].astype(str)
+            data["currency"] = "USD"
+            data = data[
+                [
+                    "name",
+                    "price",
+                    "prev_close",
+                    "change",
+                    "change_percent",
+                    "open",
+                    "high",
+                    "low",
+                    "close",
+                    "currency",
+                    "last_trade_timestamp",
+                ]
+            ]
+
+        if query.region == "EU":
+            r = make_request(
+                "https://cdn.cboe.com/api/global/european_indices/index_quotes/all-indices.json"
+            )
+
+            if r.status_code != 200:
+                raise RuntimeError(r.status_code)
+
+            data = (
+                pd.DataFrame.from_records(r.json()["data"])
+                .drop(columns=["symbol"])
+                .rename(columns={"index": "symbol"})
+                .set_index("symbol")
+                .round(2)
+            )
+
+            INDEXES = pd.DataFrame(Europe.list_indices()).set_index("symbol")
+
+            for i in data.index:
+                data.loc[i, ("isin")] = INDEXES.at[i, "isin"]
+                data.loc[i, ("name")] = INDEXES.at[i, "name"]
+                data.loc[i, ("currency")] = INDEXES.at[i, "currency"]
+
+            data = data[list(EUR_INDEX_COLUMNS.keys())]
+            data.columns = list(EUR_INDEX_COLUMNS.values())
+
+        return data.reset_index().to_dict("records")
+
+    @staticmethod
+    def transform_data(data: dict) -> List[CboeIndexSnapshotsData]:
+        """Transform the data to the standard format"""
+        return [CboeIndexSnapshotsData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/major_indices_historical.py b/openbb_sdk/providers/cboe/openbb_cboe/models/major_indices_historical.py
new file mode 100644
index 00000000000..f7a0f9060a8
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/major_indices_historical.py
@@ -0,0 +1,212 @@
+"""CBOE Major Indices End of Day fetcher."""
+
+from datetime import datetime, timedelta
+from typing import Any, Dict, List, Literal, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.major_indices_historical import (
+    MajorIndicesHistoricalData,
+    MajorIndicesHistoricalQueryParams,
+)
+from openbb_provider.utils.helpers import make_request
+from pydantic import Field
+
+from openbb_cboe.utils.helpers import (
+    TICKER_EXCEPTIONS,
+    get_cboe_index_directory,
+    get_ticker_info,
+)
+
+
+class CboeMajorIndicesHistoricalQueryParams(MajorIndicesHistoricalQueryParams):
+    """CBOE Stock end of day query.
+
+    Source: https://www.cboe.com/
+    """
+
+    interval: Optional[Literal["1d", "1m"]] = Field(
+        description="Use interval, 1m, for intraday prices during the most recent trading period.",
+        default="1d",
+    )
+
+
+class CboeMajorIndicesHistoricalData(MajorIndicesHistoricalData):
+    """CBOE Stocks End of Day Data."""
+
+    calls_volume: Optional[float] = Field(
+        description="Number of calls traded during the most recent trading period. Only valid if interval is 1m."
+    )
+    puts_volume: Optional[float] = Field(
+        description="Number of puts traded during the most recent trading period. Only valid if interval is 1m."
+    )
+    total_options_volume: Optional[float] = Field(
+        description="Total number of options traded during the most recent trading period. Only valid if interval is 1m."
+    )
+
+
+class CboeMajorIndicesHistoricalFetcher(
+    Fetcher[
+        CboeMajorIndicesHistoricalQueryParams,
+        CboeMajorIndicesHistoricalData,
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(
+        params: Dict[str, Any]
+    ) -> CboeMajorIndicesHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        return CboeMajorIndicesHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeMajorIndicesHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        # Synbol directories are cached for seven days and are used for error handling and URL generation.
+        INDEXES = get_cboe_index_directory().index.to_list()
+        query.symbol = query.symbol.upper()
+        data = pd.DataFrame()
+        if "^" in query.symbol:
+            query.symbol = query.symbol.replace("^", "")
+        if query.symbol == "NDX" and query.interval == "1d":
+            raise RuntimeError(
+                "NDX time series data is only supported when `interval='1m'`."
+            )
+
+        now = datetime.now()
+        query.start_date = (
+            query.start_date if query.start_date else now - timedelta(days=50000)
+        )
+        query.end_date = query.end_date if query.end_date else now
+
+        if query.symbol not in INDEXES and query.symbol not in TICKER_EXCEPTIONS:
+            raise RuntimeError(
+                f"The symbol, {query.symbol}, was not found in the CBOE index directory. "
+                "Use `index_search()` to find supported indices. If the index is European, try `european_index()`."
+            )
+
+        def __generate_historical_prices_url(
+            symbol,
+            data_type: Optional[Literal["intraday", "historical"]] = "historical",
+        ) -> str:
+            """Generate the final URL for historical prices data."""
+            url: str = (
+                f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}"
+            )
+            url = (
+                url + f"/_{symbol}.json"
+                if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
+                else url + f"/{symbol}.json"
+            )
+            return url
+
+        url = (
+            __generate_historical_prices_url(query.symbol, "intraday")
+            if query.interval == "1m"
+            else __generate_historical_prices_url(query.symbol)
+        )
+        r = make_request(url)
+
+        if r.status_code != 200:
+            raise RuntimeError(r.status_code)
+
+        if query.interval == "1d":
+            data = (
+                pd.DataFrame(r.json()["data"])[
+                    ["date", "open", "high", "low", "close", "volume"]
+                ]
+            ).set_index("date")
+
+            # Fill in missing data from current or most recent trading session.
+
+            today = pd.to_datetime(datetime.now().date())
+            if today.weekday() > 4:
+                day_minus = today.weekday() - 4
+                today = pd.to_datetime(today - timedelta(days=day_minus))
+            if today != data.index[-1]:
+                _today = pd.Series(get_ticker_info(query.symbol))
+                today_df = pd.Series(dtype="object")
+                today_df["open"] = round(_today["open"], 2)
+                today_df["high"] = round(_today["high"], 2)
+                today_df["low"] = round(_today["low"], 2)
+                today_df["close"] = round(_today["close"], 2)
+                if (
+                    query.symbol not in INDEXES
+                    and query.symbol not in TICKER_EXCEPTIONS
+                ):
+                    data = data[data["volume"] > 0]
+                    today_df["volume"] = _today["volume"]
+                today_df["date"] = today.date()
+                today_df = pd.DataFrame(today_df).transpose().set_index("date")
+
+                data = pd.concat([data, today_df], axis=0)
+
+            # If ticker is an index there is no volume data and the types must be set.
+
+            if query.symbol in INDEXES or query.symbol in TICKER_EXCEPTIONS:
+                data = data[["open", "high", "low", "close", "volume"]]
+                data["open"] = round(data.open.astype(float), 2)
+                data["high"] = round(data.high.astype(float), 2)
+                data["low"] = round(data.low.astype(float), 2)
+                data["close"] = round(data.close.astype(float), 2)
+                data["volume"] = 0
+
+            data.index = pd.to_datetime(data.index, format="%Y-%m-%d")
+            data = data[data["open"] > 0]
+
+            data = data[
+                (data.index >= pd.to_datetime(query.start_date, format="%Y-%m-%d"))
+                & (data.index <= pd.to_datetime(query.end_date, format="%Y-%m-%d"))
+            ]
+            data.index = data.index.astype(str)
+
+        if query.interval == "1m":
+            data_list = r.json()["data"]
+            date: List[datetime] = []
+            open: List[float] = []
+            high: List[float] = []
+            low: List[float] = []
+            close: List[float] = []
+            volume: List[float] = []
+            calls_volume: List[float] = []
+            puts_volume: List[float] = []
+            total_options_volume: List[float] = []
+
+            for i in range(0, len(data_list)):
+                date.append(data_list[i]["datetime"])
+                open.append(data_list[i]["price"]["open"])
+                high.append(data_list[i]["price"]["high"])
+                low.append(data_list[i]["price"]["low"])
+                close.append(data_list[i]["price"]["close"])
+                volume.append(data_list[i]["volume"]["stock_volume"])
+                calls_volume.append(data_list[i]["volume"]["calls_volume"])
+                puts_volume.append(data_list[i]["volume"]["puts_volume"])
+                total_options_volume.append(
+                    data_list[i]["volume"]["total_options_volume"]
+                )
+            data = pd.DataFrame()
+            data["date"] = pd.to_datetime(date)
+            data["open"] = open
+            data["high"] = high
+            data["low"] = low
+            data["close"] = close
+            data["volume"] = volume
+            data["calls_volume"] = calls_volume
+            data["puts_volume"] = puts_volume
+            data["total_options_volume"] = total_options_volume
+            data = data.set_index("date").sort_index()
+            data.index = data.index.astype(str)
+            data = data[data["open"] > 0]
+
+        return data.reset_index().to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[CboeMajorIndicesHistoricalData]:
+        """Transform the data to the standard format"""
+        return [CboeMajorIndicesHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/options_chains.py b/openbb_sdk/providers/cboe/openbb_cboe/models/options_chains.py
index 5afcc22426b..25f7929a576 100644
--- a/openbb_sdk/providers/cboe/openbb_cboe/models/options_chains.py
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/options_chains.py
@@ -4,18 +4,24 @@
 from datetime import datetime
 from typing import Any, Dict, List, Optional
 
+import pandas as pd
 from openbb_provider.abstract.fetcher import Fetcher
 from openbb_provider.standard_models.options_chains import (
     OptionsChainsData,
     OptionsChainsQueryParams,
 )
+from openbb_provider.utils.helpers import make_request
 from pydantic import Field, validator
 
-from openbb_cboe.utils.helpers import get_chains
+from openbb_cboe.utils.helpers import (
+    TICKER_EXCEPTIONS,
+    get_cboe_directory,
+    get_cboe_index_directory,
+)
 
 
 class CboeOptionsChainsQueryParams(OptionsChainsQueryParams):
-    """CBOE Options Chains query.
+    """Get the complete options chains for a ticker from CBOE.
 
     Source: https://www.cboe.com/
     """
@@ -24,36 +30,12 @@ class CboeOptionsChainsQueryParams(OptionsChainsQueryParams):
 class CboeOptionsChainsData(OptionsChainsData):
     """CBOE Options Chains Data."""
 
-    contract_symbol: str = Field(
-        description="Contract symbol for the option.",
-    )
-    dte: int = Field(
-        description="Days to expiration for the option.",
-    )
     bid_size: int = Field(
         description="Bid size for the option.",
     )
     ask_size: int = Field(
         description="Ask size for the option.",
     )
-    implied_volatility: float = Field(
-        description="Implied volatility of the option.",
-    )
-    delta: float = Field(
-        description="Delta of the option.",
-    )
-    gamma: float = Field(
-        description="Gamma of the option.",
-    )
-    theta: float = Field(
-        description="Theta of the option.",
-    )
-    rho: float = Field(
-        description="Rho of the option.",
-    )
-    vega: float = Field(
-        description="Vega of the option.",
-    )
     theoretical: float = Field(
         description="Theoretical value of the option.",
     )
@@ -72,7 +54,7 @@ class CboeOptionsChainsData(OptionsChainsData):
     tick: str = Field(
         description="Whether the last tick was up or down in price.",
     )
-    previous_close: float = Field(
+    prev_close: float = Field(
         description="Previous closing price of the option.",
     )
     change: float = Field(
@@ -81,9 +63,30 @@ class CboeOptionsChainsData(OptionsChainsData):
     change_percent: float = Field(
         description="Change, in percent, of the option.",
     )
+    implied_volatility: float = Field(
+        description="Implied volatility of the option.",
+    )
+    delta: float = Field(
+        description="Delta of the option.",
+    )
+    gamma: float = Field(
+        description="Gamma of the option.",
+    )
+    vega: float = Field(
+        description="Vega of the option.",
+    )
+    theta: float = Field(
+        description="Theta of the option.",
+    )
+    rho: float = Field(
+        description="Rho of the option.",
+    )
     last_trade_timestamp: datetime = Field(
         description="Last trade timestamp of the option.",
     )
+    dte: int = Field(
+        description="Days to expiration for the option.",
+    )
 
     @validator("expiration", pre=True, check_fields=False)
     def date_validate(cls, v):  # pylint: disable=E0213
@@ -109,9 +112,86 @@ class CboeOptionsChainsFetcher(
         query: CboeOptionsChainsQueryParams,
         credentials: Optional[Dict[str, str]],
         **kwargs: Any,
-    ) -> dict:
+    ) -> List[Dict]:
         """Return the raw data from the CBOE endpoint"""
-        return get_chains(query.symbol).to_dict("records")
+
+        symbol = query.symbol.upper()
+
+        INDEXES = get_cboe_index_directory()
+        SYMBOLS = get_cboe_directory()
+
+        if symbol not in SYMBOLS.index:
+            raise RuntimeError(f"{symbol} was not found in the CBOE directory.")
+
+        quotes_url = (
+            f"https://cdn.cboe.com/api/global/delayed_quotes/options/_{symbol}.json"
+            if symbol in TICKER_EXCEPTIONS or symbol in INDEXES.index
+            else f"https://cdn.cboe.com/api/global/delayed_quotes/options/{symbol}.json"
+        )
+
+        r = make_request(quotes_url)
+        if r.status_code != 200:
+            raise RuntimeError(f"No options data found for the symbol, {symbol}.")
+
+        r_json = r.json()
+        options_df = pd.DataFrame.from_records(r_json["data"]["options"])
+
+        options_df = options_df.rename(
+            columns={
+                "option": "contract_symbol",
+                "iv": "implied_volatility",
+                "theo": "theoretical",
+                "last_trade_price": "last_trade_price",
+                "last_trade_time": "last_trade_timestamp",
+                "percent_change": "change_percent",
+                "prev_day_close": "prev_close",
+            }
+        )
+
+        # Parses the option symbols into columns for expiration, strike, and option_type
+
+        option_df_index = options_df["contract_symbol"].str.extractall(
+            r"^(?P<Ticker>\D*)(?P<expiration>\d*)(?P<option_type>\D*)(?P<strike>\d*)"
+        )
+        option_df_index = option_df_index.reset_index().drop(
+            columns=["match", "level_0"]
+        )
+        option_df_index.option_type = option_df_index.option_type.str.replace(
+            "C", "call"
+        ).str.replace("P", "put")
+        option_df_index.strike = [ele.lstrip("0") for ele in option_df_index.strike]
+        option_df_index.strike = pd.Series(option_df_index.strike).astype(float)
+        option_df_index.strike = option_df_index.strike * (1 / 1000)
+        option_df_index.strike = option_df_index.strike.to_list()
+        option_df_index.expiration = [
+            ele.lstrip("1") for ele in option_df_index.expiration
+        ]
+        option_df_index.expiration = pd.DatetimeIndex(
+            option_df_index.expiration, yearfirst=True
+        ).astype(str)
+        option_df_index = option_df_index.drop(columns=["Ticker"])
+
+        # Joins the parsed symbol into the dataframe.
+
+        quotes = option_df_index.join(options_df)
+
+        now = datetime.now()
+        temp = pd.DatetimeIndex(quotes.expiration)
+        temp_ = (temp - now).days + 1
+        quotes["dte"] = temp_
+
+        quotes["last_trade_timestamp"] = pd.to_datetime(quotes["last_trade_timestamp"])
+        quotes = quotes.set_index(
+            keys=["expiration", "strike", "option_type"]
+        ).sort_index()
+        quotes["open_interest"] = quotes["open_interest"].astype("int64")
+        quotes["volume"] = quotes["volume"].astype("int64")
+        quotes["bid_size"] = quotes["bid_size"].astype("int64")
+        quotes["ask_size"] = quotes["ask_size"].astype("int64")
+        quotes["prev_close"] = round(quotes["prev_close"], 2)
+        quotes["change_percent"] = round(quotes["change_percent"], 2)
+
+        return quotes.reset_index().to_dict("records")
 
     @staticmethod
     def transform_data(
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/stock_historical.py b/openbb_sdk/providers/cboe/openbb_cboe/models/stock_historical.py
new file mode 100644
index 00000000000..8d91be12e83
--- /dev/null
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/stock_historical.py
@@ -0,0 +1,210 @@
+"""CBOE Major Indices End of Day fetcher."""
+
+from datetime import datetime, timedelta
+from typing import Any, Dict, List, Literal, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_historical import (
+    StockHistoricalData,
+    StockHistoricalQueryParams,
+)
+from openbb_provider.utils.helpers import make_request
+from pydantic import Field
+
+from openbb_cboe.utils.helpers import (
+    TICKER_EXCEPTIONS,
+    get_cboe_directory,
+    get_cboe_index_directory,
+    get_ticker_info,
+)
+
+
+class CboeStockHistoricalQueryParams(StockHistoricalQueryParams):
+    """CBOE Stock end of day query.
+
+    Source: https://www.cboe.com/
+    """
+
+    interval: Optional[Literal["1d", "1m"]] = Field(
+        description="Use interval, 1m, for intraday prices during the most recent trading period.",
+        default="1d",
+    )
+
+
+class CboeStockHistoricalData(StockHistoricalData):
+    """CBOE Stocks End of Day Data."""
+
+    calls_volume: Optional[float] = Field(
+        description="Number of calls traded during the most recent trading period. Only valid if interval is 1m."
+    )
+    puts_volume: Optional[float] = Field(
+        description="Number of puts traded during the most recent trading period. Only valid if interval is 1m."
+    )
+    total_options_volume: Optional[float] = Field(
+        description="Total number of options traded during the most recent trading period. Only valid if interval is 1m."
+    )
+
+
+class CboeStockHistoricalFetcher(
+    Fetcher[
+        CboeStockHistoricalQueryParams,
+        CboeStockHistoricalData,
+    ]
+):
+    """Transform the query, extract and transform the data from the CBOE endpoints"""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> CboeStockHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        return CboeStockHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: CboeStockHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the CBOE endpoint"""
+
+        # Synbol directories are cached for seven days and are used for error handling and URL generation.
+        SYMBOLS = get_cboe_directory()
+        INDEXES = get_cboe_index_directory().index.to_list()
+        query.symbol = query.symbol.upper()
+        data = pd.DataFrame()
+        if "^" in query.symbol:
+            query.symbol = query.symbol.replace("^", "")
+        if query.symbol == "NDX" and query.interval == "1d":
+            raise RuntimeError(
+                "NDX time series data is only supported when `interval='1m'`."
+            )
+
+        now = datetime.now()
+        query.start_date = (
+            query.start_date if query.start_date else now - timedelta(days=50000)
+        )
+        query.end_date = query.end_date if query.end_date else now
+
+        if query.symbol not in SYMBOLS.index and query.symbol not in INDEXES:
+            raise RuntimeError(
+                f"The symbol, {query.symbol}, was not found in the CBOE directory.  Use `search()`."
+            )
+
+        def __generate_historical_prices_url(
+            symbol,
+            data_type: Optional[Literal["intraday", "historical"]] = "historical",
+        ) -> str:
+            """Generate the final URL for historical prices data."""
+            url: str = (
+                f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}"
+            )
+            url = (
+                url + f"/_{symbol}.json"
+                if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
+                else url + f"/{symbol}.json"
+            )
+            return url
+
+        url = (
+            __generate_historical_prices_url(query.symbol, "intraday")
+            if query.interval == "1m"
+            else __generate_historical_prices_url(query.symbol)
+        )
+        r = make_request(url)
+
+        if r.status_code != 200:
+            raise RuntimeError(r.status_code)
+
+        if query.interval == "1d":
+            data = (
+                pd.DataFrame(r.json()["data"])[
+                    ["date", "open", "high", "low", "close", "volume"]
+                ]
+            ).set_index("date")
+
+            # Fill in missing data from current or most recent trading session.
+
+            today = pd.to_datetime(datetime.now().date())
+            if today.weekday() > 4:
+                day_minus = today.weekday() - 4
+                today = pd.to_datetime(today - timedelta(days=day_minus))
+            if today != data.index[-1]:
+                _today = pd.Series(get_ticker_info(query.symbol))
+                today_df = pd.Series(dtype="object")
+                today_df["open"] = round(_today["open"], 2)
+                today_df["high"] = round(_today["high"], 2)
+                today_df["low"] = round(_today["low"], 2)
+                today_df["close"] = round(_today["close"], 2)
+                if (
+                    query.symbol not in INDEXES
+                    and query.symbol not in TICKER_EXCEPTIONS
+                ):
+                    data = data[data["volume"] > 0]
+                    today_df["volume"] = _today["volume"]
+                today_df["date"] = today.date()
+                today_df = pd.DataFrame(today_df).transpose().set_index("date")
+
+                data = pd.concat([data, today_df], axis=0)
+
+            # If ticker is an index there is no volume data and the types must be set.
+
+            if query.symbol in INDEXES or query.symbol in TICKER_EXCEPTIONS:
+                data = data[["open", "high", "low", "close", "volume"]]
+                data["open"] = round(data.open.astype(float), 2)
+                data["high"] = round(data.high.astype(float), 2)
+                data["low"] = round(data.low.astype(float), 2)
+                data["close"] = round(data.close.astype(float), 2)
+                data["volume"] = 0
+
+            data.index = pd.to_datetime(data.index, format="%Y-%m-%d")
+            data = data[data["open"] > 0]
+            data = data[
+                (data.index >= pd.to_datetime(query.start_date, format="%Y-%m-%d"))
+                & (data.index <= pd.to_datetime(query.end_date, format="%Y-%m-%d"))
+            ]
+            data.index = data.index.astype(str)
+        if query.interval == "1m":
+            data_list = r.json()["data"]
+            date: List[datetime] = []
+            open: List[float] = []
+            high: List[float] = []
+            low: List[float] = []
+            close: List[float] = []
+            volume: List[float] = []
+            calls_volume: List[float] = []
+            puts_volume: List[float] = []
+            total_options_volume: List[float] = []
+
+            for i in range(0, len(data_list)):
+                date.append(data_list[i]["datetime"])
+                open.append(data_list[i]["price"]["open"])
+                high.append(data_list[i]["price"]["high"])
+                low.append(data_list[i]["price"]["low"])
+                close.append(data_list[i]["price"]["close"])
+                volume.append(data_list[i]["volume"]["stock_volume"])
+                calls_volume.append(data_list[i]["volume"]["calls_volume"])
+                puts_volume.append(data_list[i]["volume"]["puts_volume"])
+                total_options_volume.append(
+                    data_list[i]["volume"]["total_options_volume"]
+                )
+            data = pd.DataFrame()
+            data["date"] = pd.to_datetime(date)
+            data["open"] = open
+            data["high"] = high
+            data["low"] = low
+            data["close"] = close
+            data["volume"] = volume
+            data["calls_volume"] = calls_volume
+            data["puts_volume"] = puts_volume
+            data["total_options_volume"] = total_options_volume
+            data = data.set_index("date").sort_index()
+            data.index = data.index.astype(str)
+            data = data[data["open"] > 0]
+
+        data["volume"] = round(data["volume"].astype("int64"))
+        return data.drop_duplicates().reset_index().to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[CboeStockHistoricalData]:
+        """Transform the data to the standard format"""
+        return [CboeStockHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/stock_info.py b/openbb_sdk/providers/cboe/openbb_cboe/models/stock_info.py
index d7f9d9b03ef..7778e9a9792 100644
--- a/openbb_sdk/providers/cboe/openbb_cboe/models/stock_info.py
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/stock_info.py
@@ -4,6 +4,7 @@
 from datetime import datetime
 from typing import Any, Dict, List, Optional
 
+import pandas as pd
 from openbb_provider.abstract.fetcher import Fetcher
 from openbb_provider.standard_models.stock_info import (
     StockInfoData,
@@ -11,7 +12,12 @@ from openbb_provider.standard_models.stock_info import (
 )
 from pydantic import Field
 
-from openbb_cboe.utils.helpers import get_info
+from openbb_cboe.utils.helpers import (
+    get_cboe_directory,
+    get_cboe_index_directory,
+    get_ticker_info,
+    get_ticker_iv,
+)
 
 
 class CboeStockInfoQueryParams(StockInfoQueryParams):
@@ -25,6 +31,7 @@ class CboeStockInfoData(StockInfoData):
     """CBOE Company Search Data."""
 
     type: Optional[str] = Field(description="Type of asset.")
+    exchange_id: Optional[int] = Field(description="The Exchange ID number.")
     tick: Optional[str] = Field(
         description="Whether the last sale was an up or down tick."
     )
@@ -35,43 +42,43 @@ class CboeStockInfoData(StockInfoData):
     volume: Optional[float] = Field(
         description="Stock volume for the current trading day."
     )
-    iv_thirty: Optional[float] = Field(
+    iv30: Optional[float] = Field(
         description="The 30-day implied volatility of the stock."
     )
-    iv_thirty_change: Optional[float] = Field(
+    iv30_change: Optional[float] = Field(
         description="Change in 30-day implied volatility of the stock."
     )
     last_trade_timestamp: Optional[datetime] = Field(
         description="Last trade timestamp for the stock."
     )
-    iv_thirty_one_year_high: Optional[float] = Field(
+    iv30_annual_high: Optional[float] = Field(
         description="The 1-year high of implied volatility."
     )
-    hv_thirty_one_year_high: Optional[float] = Field(
+    hv30_annual_high: Optional[float] = Field(
         description="The 1-year high of realized volatility."
     )
-    iv_thirty_one_year_low: Optional[float] = Field(
+    iv30_annual_low: Optional[float] = Field(
         description="The 1-year low of implied volatility."
     )
-    hv_thirty_one_year_low: Optional[float] = Field(
+    hv30_annual_low: Optional[float] = Field(
         description="The 1-year low of realized volatility."
     )
-    iv_sixty_one_year_high: Optional[float] = Field(
+    iv60_annual_high: Optional[float] = Field(
         description="The 60-day high of implied volatility."
     )
-    hv_sixty_one_year_high: Optional[float] = Field(
+    hv60_annual_high: Optional[float] = Field(
         description="The 60-day high of realized volatility."
     )
-    iv_sixty_one_year_low: Optional[float] = Field(
+    iv60_annual_low: Optional[float] = Field(
         description="The 60-day low of implied volatility."
     )
-    hv_sixty_one_year_low: Optional[float] = Field(
+    hv60_annual_low: Optional[float] = Field(
         description="The 60-day low of realized volatility."
     )
-    iv_ninety_one_year_high: Optional[float] = Field(
+    iv90_annual_high: Optional[float] = Field(
         description="The 90-day high of implied volatility."
     )
-    hv_ninety_one_year_high: Optional[float] = Field(
+    hv90_annual_high: Optional[float] = Field(
         description="The 90-day high of realized volatility."
     )
 
@@ -96,7 +103,26 @@ class CboeStockInfoFetcher(
         **kwargs: Any,
     ) -> dict:
         """Return the raw data from the CBOE endpoint"""
-        return get_info(query.symbol).to_dict()
+
+        query.symbol = query.symbol.upper()
+        INDEXES = get_cboe_index_directory().index.to_list()
+        SYMBOLS = get_cboe_directory()
+
+        if query.symbol not in SYMBOLS.index and query.symbol not in INDEXES:
+            raise RuntimeError(
+                f"The symbol, {query.symbol}, was not found in the CBOE directory."
+            )
+
+        _info = pd.Series(get_ticker_info(query.symbol))
+        _iv = pd.Series(get_ticker_iv(query.symbol))
+        data = (
+            pd.DataFrame(pd.concat([_info, _iv]))
+            .transpose()
+            .drop(columns="seqno")
+            .iloc[0]
+        )
+
+        return data.to_dict()
 
     @staticmethod
     def transform_data(data: dict) -> List[CboeStockInfoData]:
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/models/stock_search.py b/openbb_sdk/providers/cboe/openbb_cboe/models/stock_search.py
index c227945296b..8e23abfce53 100644
--- a/openbb_sdk/providers/cboe/openbb_cboe/models/stock_search.py
+++ b/openbb_sdk/providers/cboe/openbb_cboe/models/stock_search.py
@@ -10,7 +10,7 @@ from openbb_provider.standard_models.stock_search import (
 )
 from pydantic import Field
 
-from openbb_cboe.utils.helpers import stock_search
+from openbb_cboe.utils.helpers import get_cboe_directory
 
 
 class CboeStockSearchQueryParams(StockSearchQueryParams):
@@ -23,20 +23,9 @@ class CboeStockSearchQueryParams(StockSearchQueryParams):
 class CboeStockSearchData(StockSearchData):
     """CBOE Company Search Data."""
 
-    class Config:
-        """Pydantic alias config using fields dict"""
-
-        fields = {
-            "name": "Company Name",
-        }
-
-    dpm_name: Optional[str] = Field(
-        description="Name of the primary market maker.",
-        alias="DPM Name",
-    )
+    dpm_name: Optional[str] = Field(description="Name of the primary market maker.")
     post_station: Optional[str] = Field(
-        description="Post and station location on the CBOE trading floor.",
-        alias="Post/Station",
+        description="Post and station location on the CBOE trading floor."
     )
 
 
@@ -60,14 +49,17 @@ class CboeStockSearchFetcher(
         **kwargs: Any,
     ) -> dict:
         """Return the raw data from the CBOE endpoint."""
-        data = stock_search(query.query, ticker=query.ticker)
 
-        if "results" in data:
-            return data["results"]
+        data = {}
+        symbols = get_cboe_directory().reset_index()
+        target = "name" if not query.ticker else "symbol"
+        idx = symbols[target].str.contains(query.query, case=False)
+        result = symbols[idx].to_dict("records")
+        data.update({"results": result})
 
-        raise ValueError("No results found.")
+        return data
 
     @staticmethod
     def transform_data(data: dict) -> List[CboeStockSearchData]:
         """Transform the data to the standard format."""
-        return [CboeStockSearchData.parse_obj(d) for d in data]
+        return [CboeStockSearchData.parse_obj(d) for d in data["results"]]
diff --git a/openbb_sdk/providers/cboe/openbb_cboe/utils/helpers.py b/openbb_sdk/providers/cboe/openbb_cboe/utils/helpers.py
index 2885d343d84..b3b0341b890 100644
--- a/openbb_sdk/providers/cboe/openbb_cboe/utils/helpers.py
+++ b/openbb_sdk/providers/cboe/openbb_cboe/utils/helpers.py
@@ -1,16 +1,13 @@
 """CBOE Helpers Module."""
 
-import os
-import warnings
-from datetime import date, datetime, timedelta
-from io import StringIO
-from pathlib import Path
-from typing import List, Optional, Tuple
+from datetime import date, timedelta
+from io import BytesIO, StringIO
+from typing import Any, Dict, List, Optional
 
-import numpy as np
 import pandas as pd
 import requests
 import requests_cache
+from openbb_provider.utils.helpers import to_snake_case
 
 TICKER_EXCEPTIONS = ["NDX", "RUT"]
 # This will cache the import requests for 7 days.  Ideally to speed up subsequent imports.
@@ -19,71 +16,62 @@ cboe_session = requests_cache.CachedSession(
     "OpenBB_CBOE", expire_after=timedelta(days=7), use_cache_dir=True
 )
 
+US_INDEX_COLUMNS = {
+    "symbol": "symbol",
+    "name": "name",
+    "current_price": "price",
+    "open": "open",
+    "high": "high",
+    "low": "low",
+    "close": "close",
+    "prev_day_close": "prev_close",
+    "price_change": "change",
+    "price_change_percent": "change_percent",
+    "last_trade_time": "last_trade_timestamp",
+}
 
-def get_user_agent() -> str:
-    """Get a not very random user agent."""
-    user_agent_strings = [
-        "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.10; rv:86.1) Gecko/20100101 Firefox/86.1",
-        "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:86.1) Gecko/20100101 Firefox/86.1",
-        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.10; rv:82.1) Gecko/20100101 Firefox/82.1",
-        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.13; rv:86.0) Gecko/20100101 Firefox/86.0",
-        "Mozilla/5.0 (Windows NT 10.0; WOW64; rv:86.0) Gecko/20100101 Firefox/86.0",
-        "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.10; rv:83.0) Gecko/20100101 Firefox/83.0",
-        "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:84.0) Gecko/20100101 Firefox/84.0",
-    ]
+EUR_INDEX_COLUMNS = {
+    "name": "name",
+    "isin": "isin",
+    "currency": "currency",
+    "current_price": "price",
+    "open": "open",
+    "high": "high",
+    "low": "low",
+    "close": "close",
+    "prev_day_close": "prev_close",
+    "price_change": "change",
+    "price_change_percent": "change_percent",
+    "last_trade_time": "last_trade_timestamp",
+}
 
-    return np.random.choice(user_agent_strings)  # nosec
+EUR_INDEX_CONSTITUENTS_COLUMNS = {
+    "symbol": "symbol",
+    "current_price": "price",
+    "open": "open",
+    "high": "high",
+    "low": "low",
+    "close": "close",
+    "volume": "volume",
+    "seqno": "seqno",
+    "prev_day_close": "prev_close",
+    "price_change": "change",
+    "price_change_percent": "change_percent",
+    "last_trade_time": "last_trade_timestamp",
+    "exchange_id": "exchange_id",
+    "tick": "tick",
+    "security_type": "type",
+}
 
 
-def request(
-    url: str, method: str = "GET", timeout: int = 10, **kwargs
-) -> requests.Response:
-    """Abstract helper to make requests from a url with potential headers and params.
-
-    Parameters
-    ----------
-    url : str
-        Url to make the request to
-    method : str, optional
-        HTTP method to use.  Can be "GET" or "POST", by default "GET"
-    timeout : int, optional
-        Timeout in seconds, by default 10
-
-    Returns
-    -------
-    requests.Response
-        Request response object
-
-    Raises
-    ------
-    ValueError
-        If invalid method is passed
-    """
-
-    # If there are headers, check if there is a user agent, if not add one.
-    # Some requests seem to work only with a specific user agent, so we want to be able to override it.
-    headers = kwargs.pop("headers", {})
-
-    if "User-Agent" not in headers:
-        headers["User-Agent"] = get_user_agent()
-
-    if (func := getattr(requests, method.lower(), None)) is not None:
-        return func(
-            url,
-            headers=headers,
-            timeout=timeout,
-            **kwargs,
-        )
-
-    raise ValueError("Method must be valid HTTP method")
+# This will cache certain requests for 7 days.  Ideally to speed up subsequent queries.
+# Only used on functions with static values like symbol directories.
+cboe_session = requests_cache.CachedSession(
+    "OpenBB_CBOE", expire_after=timedelta(days=7), use_cache_dir=True
+)
 
 
-def camel_to_snake(string: str) -> str:
-    """Convert camelCase to snake_case."""
-    return "".join(["_" + i.lower() if i.isupper() else i for i in string]).lstrip("_")
-
-
-def get_cboe_directory() -> pd.DataFrame:
+def get_cboe_directory(**kwargs) -> pd.DataFrame:
     """Get the US Listings Directory for the CBOE.
 
     Returns
@@ -91,276 +79,133 @@ def get_cboe_directory() -> pd.DataFrame:
     pd.DataFrame: CBOE_DIRECTORY
         DataFrame of the CBOE listings directory
     """
-    try:
-        CBOE_DIRECTORY: pd.DataFrame = pd.read_csv(
-            StringIO(
-                cboe_session.get(
-                    "https://www.cboe.com/us/options/symboldir/equity_index_options/?download=csv",
-                    timeout=10,
-                ).text
-            )
-        )
-        CBOE_DIRECTORY = CBOE_DIRECTORY.rename(
-            columns={
-                " Stock Symbol": "Symbol",
-                " DPM Name": "DPM Name",
-                " Post/Station": "Post/Station",
-            }
-        ).set_index("Symbol")
-        return CBOE_DIRECTORY
-    except requests.HTTPError:
-        return pd.DataFrame()
+
+    r = cboe_session.get(
+        "https://www.cboe.com/us/options/symboldir/equity_index_options/?download=csv",
+        timeout=10,
+    )
+
+    if r.status_code != 200:
+        raise RuntimeError(r.status_code)
+
+    r_json = StringIO(r.text)
+
+    CBOE_DIRECTORY = pd.read_csv(r_json)
+
+    CBOE_DIRECTORY = CBOE_DIRECTORY.rename(
+        columns={
+            " Stock Symbol": "symbol",
+            " DPM Name": "dpm_name",
+            " Post/Station": "post_station",
+            "Company Name": "name",
+        }
+    ).set_index("symbol")
+
+    return CBOE_DIRECTORY
 
 
-def get_cboe_index_directory() -> pd.DataFrame:
+def get_cboe_index_directory(**kwargs) -> pd.DataFrame:
     """Get the US Listings Directory for the CBOE
 
     Returns
     -------
     pd.DataFrame: CBOE_INDEXES
     """
-    try:
-        r = cboe_session.get(
-            "https://cdn.cboe.com/api/global/us_indices/definitions/all_indices.json",
-            timeout=10,
-        )
 
-        if r.status_code != 200:
-            raise requests.HTTPError
+    r = cboe_session.get(
+        "https://cdn.cboe.com/api/global/us_indices/definitions/all_indices.json",
+        timeout=10,
+    )
 
-        CBOE_INDEXES = pd.DataFrame(r.json())
+    if r.status_code != 200:
+        raise requests.HTTPError(r.status_code)
 
-        CBOE_INDEXES = CBOE_INDEXES.rename(
-            columns={
-                "calc_end_time": "Close Time",
-                "calc_start_time": "Open Time",
-                "currency": "Currency",
-                "description": "Description",
-                "display": "Display",
-                "featured": "Featured",
-                "featured_order": "Featured Order",
-                "index_symbol": "Ticker",
-                "mkt_data_delay": "Data Delay",
-                "name": "Name",
-                "tick_days": "Tick Days",
-                "tick_frequency": "Frequency",
-                "tick_period": "Period",
-                "time_zone": "Time Zone",
-            },
-        )
+    CBOE_INDEXES = pd.DataFrame(r.json())
 
-        indices_order: List[str] = [
-            "Ticker",
-            "Name",
-            "Description",
-            "Currency",
-            "Tick Days",
-            "Frequency",
-            "Period",
-            "Time Zone",
-        ]
+    CBOE_INDEXES = CBOE_INDEXES.rename(
+        columns={
+            "calc_end_time": "close_time",
+            "calc_start_time": "open_time",
+            "index_symbol": "symbol",
+            "mkt_data_delay": "data_delay",
+        },
+    )
 
-        CBOE_INDEXES = pd.DataFrame(CBOE_INDEXES, columns=indices_order).set_index(
-            "Ticker"
-        )
+    indices_order: List[str] = [
+        "symbol",
+        "name",
+        "description",
+        "currency",
+        "open_time",
+        "close_time",
+        "tick_days",
+        "tick_frequency",
+        "tick_period",
+        "time_zone",
+        "data_delay",
+    ]
 
-        return CBOE_INDEXES
+    CBOE_INDEXES = pd.DataFrame(CBOE_INDEXES, columns=indices_order).set_index("symbol")
 
-    except requests.HTTPError:
-        return pd.DataFrame()
+    idx = (
+        (CBOE_INDEXES.time_zone.str.contains("America/Chicago"))
+        & (CBOE_INDEXES.currency.str.contains("USD"))
+        & (CBOE_INDEXES.description.str.contains("Daily Risk Control") == 0)
+        & (CBOE_INDEXES.name.str.contains("OEX%-SML% INDEX") == 0)
+        & (CBOE_INDEXES.name.str.contains("Defined Risk Volatility Income") == 0)
+        & (CBOE_INDEXES.description.str.contains("is designed to track") == 0)
+    )
+
+    return CBOE_INDEXES[idx]
 
 
-INDEXES = get_cboe_index_directory().index.tolist()
-SYMBOLS = pd.DataFrame()
-try:
-    SYMBOLS = get_cboe_directory()
-except SYMBOLS.empty:
-    current_dir = os.path.dirname(os.path.realpath(__file__))
-    file = "cboe_companies.json"
-    SYMBOLS = pd.read_json(Path(current_dir, file))
-
-
-def stock_search(query: str, ticker: bool = False) -> dict:
-    """Search the CBOE company directory by name or ticker.
-    Parameters
-    -----------
-    query: str
-        The search query
-    ticker: bool
-        Whether to search by ticker. Default is False.
-
-    Returns
-    -------
-    dict
-        Dictionary of the results.
-    """
-    data = {}
-    symbols = SYMBOLS.copy() if not SYMBOLS.empty else get_cboe_directory()
-    symbols = symbols.reset_index()
-    target = "Company Name" if not ticker else "Symbol"
-    idx = symbols[target].str.contains(query, case=False)
-    result = symbols[idx].to_dict("records")
-    if len(result) > 0:
-        data.update({"results": result})
-        return data
-    warnings.warn(f"No results found for: {query}.  Try another search query.")
-    return pd.DataFrame()
-
-
-def get_ticker_info(symbol: str) -> Tuple[pd.DataFrame, List[str]]:
-    """Get basic info for the symbol and expiration dates
-
-    Parameters
-    ----------
-    symbol: str
-        The ticker to lookup
-
-    Returns
-    -------
-    Tuple: [pd.DataFrame, pd.Series]
-        ticker_details
-        ticker_expirations
-    """
-
-    stock = "stock"
-    index = "index"
+def get_ticker_info(symbol: str, **kwargs) -> dict[str, Any]:
     symbol = symbol.upper()
-    new_ticker: str = ""
-    ticker_details = pd.DataFrame()
-    ticker_expirations: list = []
-    try:
-        if symbol in TICKER_EXCEPTIONS:
-            new_ticker = "^" + symbol
-        elif symbol not in INDEXES:
-            new_ticker = symbol
+    SYMBOLS = get_cboe_directory()
+    INDEXES = get_cboe_index_directory()
+    data: dict[str, Any] = {}
 
-        elif symbol in INDEXES:
-            new_ticker = "^" + symbol
+    if symbol not in SYMBOLS.index and symbol not in INDEXES.index:
+        raise RuntimeError(f"Data not found for: {symbol}")
 
-            # Get the data to return, and if none returns empty Tuple #
+    url = (
+        f"https://cdn.cboe.com/api/global/delayed_quotes/quotes/_{symbol}.json"
+        if symbol in INDEXES.index or symbol in TICKER_EXCEPTIONS
+        else f"https://cdn.cboe.com/api/global/delayed_quotes/quotes/{symbol}.json"
+    )
 
-        symbol_info_url = (
-            "https://www.cboe.com/education/tools/trade-optimizer/symbol-info/?symbol="
-            f"{new_ticker}"
-        )
+    r = requests.get(url, timeout=10)
 
-        symbol_info = request(symbol_info_url)
-        symbol_info_json = pd.Series(symbol_info.json())
+    if r.status_code not in set([200, 403]):
+        raise requests.HTTPError(r.status_code)
 
-        if symbol_info_json.success is False:
-            ticker_details = pd.DataFrame()
-            ticker_expirations = []
-            warnings.warn("No data found for the symbol: " f"{symbol}" "")
-        else:
-            symbol_details = pd.Series(symbol_info_json["details"])
-            symbol_details = pd.DataFrame(symbol_details).transpose()
-            symbol_details = symbol_details.reset_index()
-            ticker_expirations = symbol_info_json["expirations"]
+    if r.status_code == 403:
+        raise RuntimeError(f"Data was not found for, {symbol}.")
 
-            # Cleans columns depending on if the security type is a stock or an index
+    data = r.json()["data"]
 
-            type_ = symbol_details.security_type
+    if symbol in SYMBOLS.index.to_list():
+        data.update({"name": SYMBOLS.at[symbol, "name"]})
+    if symbol in INDEXES.index.to_list():
+        data.update({"name": INDEXES.at[symbol, "name"]})
 
-            if stock[0] in type_[0]:
-                stock_details = symbol_details
-                ticker_details = pd.DataFrame(stock_details).rename(
-                    columns={
-                        "current_price": "price",
-                        "bid_size": "bidSize",
-                        "ask_size": "askSize",
-                        "iv30": "ivThirty",
-                        "prev_day_close": "previousClose",
-                        "price_change": "change",
-                        "price_change_percent": "changePercent",
-                        "iv30_change": "ivThirtyChange",
-                        "iv30_percent_change": "ivThirtyChangePercent",
-                        "last_trade_time": "lastTradeTimestamp",
-                        "exchange_id": "exchangeID",
-                        "tick": "tick",
-                        "security_type": "type",
-                    }
-                )
-                details_columns = [
-                    "symbol",
-                    "type",
-                    "tick",
-                    "bid",
-                    "bidSize",
-                    "askSize",
-                    "ask",
-                    "price",
-                    "open",
-                    "high",
-                    "low",
-                    "close",
-                    "volume",
-                    "previousClose",
-                    "change",
-                    "changePercent",
-                    "ivThirty",
-                    "ivThirtyChange",
-                    "ivThirtyChangePercent",
-                    "lastTradeTimestamp",
-                ]
-                ticker_details = (
-                    pd.DataFrame(ticker_details, columns=details_columns)
-                    .set_index(keys="symbol")
-                    .dropna(axis=1)
-                    .transpose()
-                )
+    _data = pd.DataFrame.from_dict(data, orient="index").transpose()
 
-            if index[0] in type_[0]:
-                index_details = symbol_details
-                ticker_details = pd.DataFrame(index_details).rename(
-                    columns={
-                        "symbol": "symbol",
-                        "security_type": "type",
-                        "current_price": "price",
-                        "price_change": "change",
-                        "price_change_percent": "changePercent",
-                        "prev_day_close": "previousClose",
-                        "iv30": "ivThirty",
-                        "iv30_change": "ivThirtyChange",
-                        "iv30_change_percent": "ivThirtyChangePercent",
-                        "last_trade_time": "lastTradeTimestamp",
-                    }
-                )
+    _data = _data.rename(
+        columns={
+            "current_price": "price",
+            "prev_day_close": "prev_close",
+            "price_change": "change",
+            "price_change_percent": "change_percent",
+            "last_trade_time": "last_trade_timestamp",
+            "security_type": "type",
+        }
+    )
 
-                index_columns = [
-                    "symbol",
-                    "type",
-                    "tick",
-                    "price",
-                    "open",
-                    "high",
-                    "low",
-                    "close",
-                    "previousClose",
-                    "change",
-                    "changePercent",
-                    "ivThirty",
-                    "ivThirtyChange",
-                    "ivThirtyChangePercent",
-                    "lastTradeTimestamp",
-                ]
-
-                ticker_details = (
-                    pd.DataFrame(ticker_details, columns=index_columns)
-                    .set_index(keys="symbol")
-                    .dropna(axis=1)
-                    .transpose()
-                ).rename(columns={f"{new_ticker}": f"{symbol}"})
-
-    except requests.HTTPError:
-        warnings.warn("There was an error with the request'\n")
-        ticker_details = pd.DataFrame()
-        ticker_expirations = list()
-        return ticker_details, ticker_expirations
-
-    return ticker_details, ticker_expirations
+    return _data.transpose()[0].to_dict()
 
 
-def get_ticker_iv(symbol: str) -> pd.DataFrame:
+def get_ticker_iv(symbol: str, **kwargs) -> dict[str, float]:
     """Get annualized high/low historical and implied volatility over 30/60/90 day windows.
 
     Parameters
@@ -373,341 +218,186 @@ def get_ticker_iv(symbol: str) -> pd.DataFrame:
     pd.DataFrame: ticker_iv
     """
 
-    # Checks ticker to determine if ticker is an index or an exception that requires modifying the request's URLs
+    symbol = symbol.upper()
 
-    try:
-        if symbol in TICKER_EXCEPTIONS:
-            quotes_iv_url = (
-                "https://cdn.cboe.com/api/global/delayed_quotes/historical_data/_"
-                f"{symbol}"
-                ".json"
-            )
-        elif symbol not in INDEXES:
-            quotes_iv_url = (
-                "https://cdn.cboe.com/api/global/delayed_quotes/historical_data/"
-                f"{symbol}"
-                ".json"
-            )
+    INDEXES = get_cboe_index_directory().index.to_list()
 
-        elif symbol in INDEXES:
-            quotes_iv_url = (
-                "https://cdn.cboe.com/api/global/delayed_quotes/historical_data/_"
-                f"{symbol}"
-                ".json"
-            )
-        h_iv = request(quotes_iv_url)
+    quotes_iv_url = (
+        "https://cdn.cboe.com/api/global/delayed_quotes/historical_data/_"
+        f"{symbol}"
+        ".json"
+        if symbol in TICKER_EXCEPTIONS or symbol in INDEXES
+        else f"https://cdn.cboe.com/api/global/delayed_quotes/historical_data/{symbol}.json"
+    )
 
-        if h_iv.status_code != 200:
-            warnings.warn("No data found for the symbol: " f"{symbol}" "")
-            return pd.DataFrame()
+    h_iv = requests.get(quotes_iv_url, timeout=10)
 
-        data = h_iv.json()
-        h_data = pd.DataFrame(data)[2:-1]["data"].rename(f"{symbol}")
-        h_data.rename(
-            {
-                "hv30_annual_high": "hvThirtyOneYearHigh",
-                "hv30_annual_low": "hvThirtyOneYearLow",
-                "hv60_annual_high": "hvSixtyOneYearHigh",
-                "hv60_annual_low": "hvSixtyOneYearLow",
-                "hv90_annual_high": "hvNinetyOneYearHigh",
-                "hv90_annual_low": "hvNinetyOneYearLow",
-                "iv30_annual_high": "ivThirtyOneYearHigh",
-                "iv30_annual_low": "ivThirtyOneYearLow",
-                "iv60_annual_high": "ivSixtyOneYearHigh",
-                "iv60_annual_low": "ivSixtyOneYearLow",
-                "iv90_annual_high": "ivNinetyOneYearHigh",
-                "iv90_annual_low": "ivNinetyOneYearLow",
-            },
-            inplace=True,
-        )
+    if h_iv.status_code not in set([200, 403]):
+        raise requests.HTTPError(h_iv.status_code)
 
-        iv_order = [
-            "ivThirtyOneYearHigh",
-            "hvThirtyOneYearHigh",
-            "ivThirtyOneYearLow",
-            "hvThirtyOneYearLow",
-            "ivSixtyOneYearHigh",
-            "hvSixtyOneYearHigh",
-            "ivSixtyOneYearLow",
-            "hvSixtyOneYearLow",
-            "ivNinetyOneYearHigh",
-            "hvNinetyOneYearHigh",
-            "ivNinetyOneYearLow",
-            "hvNinetyOneYearLow",
-        ]
+    if h_iv.status_code == 403:
+        raise RuntimeError(f"Data was not found for, {symbol}.")
 
-        ticker_iv = pd.DataFrame(h_data).transpose()
-    except requests.HTTPError:
-        warnings.warn("There was an error with the request'\n")
+    data = pd.DataFrame(h_iv.json())[2:-1]["data"].rename(f"{symbol}")
 
-    return pd.DataFrame(ticker_iv, columns=iv_order).transpose()
+    return data.to_dict()
 
 
-def get_chains(symbol: str) -> pd.DataFrame:
-    """Get the complete options chains for a ticker.
-
-    Parameters
-    ----------
-    symbol: str
-        The ticker get options data for
+def list_futures(**kwargs) -> List[dict]:
+    """List of CBOE futures and their underlying symbols.
 
     Returns
-    -------
+    --------
     pd.DataFrame
-        DataFrame with all active options contracts for the underlying symbol.
+        Pandas DataFrame with results.
     """
 
-    # Checks ticker to determine if ticker is an index or an exception that requires modifying the request's URLs.
-    symbol = symbol.upper()
-    try:
-        if symbol in TICKER_EXCEPTIONS:
-            quotes_url = (
-                "https://cdn.cboe.com/api/global/delayed_quotes/options/_"
-                f"{symbol}"
-                ".json"
-            )
-        else:
-            if symbol not in INDEXES:
-                quotes_url = (
-                    "https://cdn.cboe.com/api/global/delayed_quotes/options/"
-                    f"{symbol}"
-                    ".json"
-                )
-            if symbol in INDEXES:
-                quotes_url = (
-                    "https://cdn.cboe.com/api/global/delayed_quotes/options/_"
-                    f"{symbol}"
-                    ".json"
-                )
+    r = requests.get(
+        "https://cdn.cboe.com/api/global/delayed_quotes/symbol_book/futures-roots.json",
+        timeout=10,
+    )
 
-        result = request(quotes_url)
-        if result.status_code != 200:
-            warnings.warn("No data found for the symbol: " f"{symbol}" "")
-            return pd.DataFrame()
+    if r.status_code != 200:
+        raise requests.HTTPError(r.status_code)
 
-        r_json = result.json()
-        data = pd.DataFrame(r_json["data"])
-        options = pd.Series(data.options, index=data.index)
-        options_columns = list(options[0])
-        options_data = list(options[:])
-        options_df = pd.DataFrame(options_data, columns=options_columns)
-
-        options_df = options_df.rename(
-            columns={
-                "option": "contractSymbol",
-                "bid_size": "bidSize",
-                "ask_size": "askSize",
-                "iv": "impliedVolatility",
-                "open_interest": "openInterest",
-                "theo": "theoretical",
-                "last_trade_price": "lastTradePrice",
-                "last_trade_time": "lastTradeTimestamp",
-                "percent_change": "changePercent",
-                "prev_day_close": "previousClose",
-            }
-        )
-
-        # Parses the option symbols into columns for expiration, strike, and optionType
-
-        option_df_index = options_df["contractSymbol"].str.extractall(
-            r"^(?P<Ticker>\D*)(?P<expiration>\d*)(?P<optionType>\D*)(?P<strike>\d*)"
-        )
-        option_df_index = option_df_index.reset_index().drop(
-            columns=["match", "level_0"]
-        )
-        option_df_index.optionType = option_df_index.optionType.str.replace(
-            "C", "call"
-        ).str.replace("P", "put")
-        option_df_index.strike = [ele.lstrip("0") for ele in option_df_index.strike]
-        option_df_index.strike = pd.Series(option_df_index.strike).astype(float)
-        option_df_index.strike = option_df_index.strike * (1 / 1000)
-        option_df_index.strike = option_df_index.strike.to_list()
-        option_df_index.expiration = [
-            ele.lstrip("1") for ele in option_df_index.expiration
-        ]
-        option_df_index.expiration = pd.DatetimeIndex(
-            option_df_index.expiration, yearfirst=True
-        ).astype(str)
-        option_df_index = option_df_index.drop(columns=["Ticker"])
-
-        # Joins the parsed symbol into the dataframe.
-
-        quotes = option_df_index.join(options_df)
-
-        now = datetime.now()
-        temp = pd.DatetimeIndex(quotes.expiration)
-        temp_ = (temp - now).days + 1
-        quotes["dte"] = temp_
-
-        quotes["lastTradeTimestamp"] = pd.to_datetime(quotes["lastTradeTimestamp"])
-        quotes = quotes.set_index(
-            keys=["expiration", "strike", "optionType"]
-        ).sort_index()
-        quotes["openInterest"] = quotes["openInterest"].astype("int64")
-        quotes["volume"] = quotes["volume"].astype("int64")
-        quotes["bidSize"] = quotes["bidSize"].astype("int64")
-        quotes["askSize"] = quotes["askSize"].astype("int64")
-        quotes["previousClose"] = round(quotes["previousClose"], 2)
-        quotes["changePercent"] = round(quotes["changePercent"], 2)
-
-    except requests.HTTPError:
-        warnings.warn("There was an error with the request'\n")
-        return pd.DataFrame()
-
-    return quotes.reset_index()
+    return r.json()["data"]
 
 
-def __generate_historical_prices_url(
-    symbol, data_type: Optional[str] = "historical"
-) -> str:
-    """Generate the final URL for historical prices data."""
-
-    url: str = ""
-
-    if data_type not in ["historical", "intraday"]:
-        warnings.warn(
-            "Invalid data_type. Must be either 'historical' or 'intraday'. Defaulting to 'historical'."
-        )
-        data_type = "historical"
-
-    if symbol in TICKER_EXCEPTIONS:
-        url = (
-            f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}/_"
-            f"{symbol}"
-            ".json"
-        )
-    elif symbol not in INDEXES:
-        url = (
-            f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}/"
-            f"{symbol}"
-            ".json"
-        )
-
-    elif symbol in INDEXES:
-        url = (
-            f"https://cdn.cboe.com/api/global/delayed_quotes/charts/{data_type}/_"
-            f"{symbol}"
-            ".json"
-        )
-    return url
-
-
-def get_eod_prices(
-    symbol: str,
-    start_date: Optional[date] = None,
-    end_date: Optional[date] = None,
+def get_settlement_prices(
+    settlement_date: Optional[date] = None,
+    options: bool = False,
+    archives: bool = False,
+    final_settlement: bool = False,
+    **kwargs,
 ) -> pd.DataFrame:
-    """Get EOD data from CBOE.
+    """Gets the settlement prices of CBOE futures.
 
     Parameters
-    ----------
-    symbol: str
-        The symbol of the company.
-    start_date: Optional[date]
-        The start date. [YYYY-MM-DD]
-    end_date: Optional[date]
-        The end date. [YYYY-MM-DD]
-
-    Returns
-    -------
-    pd.DataFrame
-        DataFrame of daily EOD OHLC+V prices.
-    """
-
-    symbol = symbol.upper()
-    if symbol == ("NDX", "^NDX"):
-        warnings.warn(
-            "NDX time series data is not currently supported by the CBOE provider."
-        )
-        return pd.DataFrame()
-    if "^" in symbol:
-        symbol = symbol.replace("^", "")
-    now = datetime.now()
-    start_date = start_date if start_date else now - timedelta(days=50000)
-    end_date = end_date if end_date else now
-    if symbol not in SYMBOLS.index:
-        warnings.warn(
-            "The symbol, " f"{symbol}" ", was not found in the CBOE directory."
-        )
-        return pd.DataFrame()
-
-    url = __generate_historical_prices_url(symbol)
-    result = request(url)
-
-    if result.status_code != 200:
-        warnings.warn(f"Error: {result.status_code}")
-        return pd.DataFrame()
-
-    data = (
-        pd.DataFrame(result.json()["data"])[
-            ["date", "open", "high", "low", "close", "volume"]
-        ]
-    ).set_index("date")
-
-    # Fill in missing data from current or most recent trading session.
-
-    today = pd.to_datetime(datetime.now().date())
-    if today.weekday() > 4:
-        day_minus = today.weekday() - 4
-        today = pd.to_datetime(today - timedelta(days=day_minus))
-    if today != data.index[-1]:
-        _today, _ = get_ticker_info(symbol)
-        today_df = pd.DataFrame()
-        today_df["open"] = round(_today.loc["open"].astype(float), 2)
-        today_df["high"] = round(_today.loc["high"].astype(float), 2)
-        today_df["low"] = round(_today.loc["low"].astype(float), 2)
-        today_df["close"] = round(_today.loc["close"].astype(float), 2)
-        if symbol not in INDEXES and symbol not in TICKER_EXCEPTIONS:
-            data = data[data["volume"] > 0]
-            today_df["volume"] = _today.loc["volume"]
-        today_df["date"] = today
-        today_df = today_df.reset_index(drop=True).set_index("date")
-
-        data = pd.concat([data, today_df], axis=0)
-
-    # If ticker is an index there is no volume data and the types must be set.
-
-    if symbol in INDEXES or symbol in TICKER_EXCEPTIONS:
-        data = data[["open", "high", "low", "close", "volume"]]
-        data["open"] = round(data.open.astype(float), 2)
-        data["high"] = round(data.high.astype(float), 2)
-        data["low"] = round(data.low.astype(float), 2)
-        data["close"] = round(data.close.astype(float), 2)
-        data["volume"] = 0
-
-    data.index = pd.to_datetime(data.index, format="%Y-%m-%d")
-    data = data[data["open"] > 0]
-
-    data = data[
-        (data.index >= pd.to_datetime(start_date, format="%Y-%m-%d"))
-        & (data.index <= pd.to_datetime(end_date, format="%Y-%m-%d"))
-    ]
-    data.index = data.index.strftime("%Y-%m-%d")
-    return data.reset_index()
-
-
-def get_info(symbol: str) -> pd.DataFrame:
-    """Get information and current statistics for a ticker.
-
-    Parameters
-    ----------
-    symbol: str
-        The symbol of the company.
+    -----------
+    settlement_date: Optional[date]
+        The settlement date. Only valid for active contracts. [YYYY-MM-DD]
+    options: bool
+        If true, returns options on futures.
+    archives: bool
+        Settlement price archives for select years and products.  Overridden by other parameters.
+    final_settlement: bool
+        Final settlement prices for expired contracts.  Overrides archives.
 
     Returns
     -------
     pd.DataFrame
         Pandas DataFrame with results.
     """
+    url = ""
+    if archives is True:
+        url = "https://cdn.cboe.com/resources/futures/archive/volume-and-price/CFE_FinalSettlement_Archive.csv"
 
-    symbol = symbol.upper()
-    info = pd.DataFrame()
+    if settlement_date is not None:
+        url = f"https://www.cboe.com/us/futures/market_statistics/settlement/csv?dt={settlement_date}"
+        if options is True:
+            url = f"https://www.cboe.com/us/futures/market_statistics/settlement/csv?options=t&dt={settlement_date}"
 
-    _info = get_ticker_info(symbol)[0]
-    _iv = get_ticker_iv(symbol)
-    info = pd.concat([_info, _iv])
-    info.index = [camel_to_snake(c) for c in info.index]
-    info.loc["symbol", symbol] = symbol
-    info.loc["name", symbol] = SYMBOLS[SYMBOLS.index == symbol]["Company Name"][0]
+    if settlement_date is None:
+        url = "https://www.cboe.com/us/futures/market_statistics/settlement/csv"
+        if options is True:
+            url = "https://www.cboe.com/us/futures/market_statistics/settlement/csv?options=t"
 
-    return info[symbol]
+    if final_settlement is True:
+        url = "https://www.cboe.com/us/futures/market_statistics/final_settlement_prices/csv/"
+
+    r = requests.get(url, timeout=10)
+
+    if r.status_code != 200:
+        raise RuntimeError(r.status_code)
+
+    data = pd.read_csv(BytesIO(r.content), index_col=None, parse_dates=True)
+
+    if data.empty:
+        error_string = (
+            f"No results found for, {settlement_date}."
+            if settlement_date is not None
+            else "No results found."
+        )
+        raise RuntimeError(error_string)
+
+    data.columns = [to_snake_case(c) for c in data.columns]
+    data = data.rename(columns={"expiration_date": "expiration"})
+
+    if len(data) > 0:
+        return data
+
+    return pd.DataFrame()
+
+
+class Europe:
+    """Class for European CBOE data."""
+
+    @staticmethod
+    def get_all_index_definitions(**kwargs) -> dict[Any, Any]:
+        """Get the full list of European index definitions.
+
+        Returns
+        -------
+        dict[Any, Any]
+            Dictionary with results.
+        """
+
+        r = cboe_session.get(
+            "https://cdn.cboe.com/api/global/european_indices/definitions/all-definitions.json",
+            timeout=10,
+        )
+
+        if r.status_code != 200:
+            raise requests.HTTPError(r.status_code)
+        return r.json()["data"]
+
+    @staticmethod
+    def list_indices(**kwargs) -> List[Dict]:
+        """Gets names, currencies, ISINs, regions, and symbols for European indices.
+
+        Returns
+        -------
+        dict[str, str]
+            List of dictionaries with the results.
+        """
+
+        data = Europe.get_all_index_definitions()
+        data = (
+            pd.DataFrame.from_records(pd.DataFrame(data)["index"])
+            .drop(columns=["short_name"])
+            .rename(columns={"long_name": "name"})
+        )
+        return data.to_dict("records")
+
+    @staticmethod
+    def list_index_constituents(symbol: str, **kwargs) -> List[str]:
+        """List symbols for constituents of a European index.
+
+        Parameters
+        ----------
+        symbol: str
+            The symbol of the index.
+
+        Returns
+        -------
+        List[str]
+            List of constituents as ticker symbols.
+        """
+
+        SYMBOLS = pd.DataFrame(Europe.list_indices())["symbol"].to_list()
+        symbol = symbol.upper()
+
+        if symbol not in SYMBOLS:
+            raise RuntimeError(
+                f"The symbol, {symbol}, was not found in the CBOE European Index directory.",
+            )
+
+        url = f"https://cdn.cboe.com/api/global/european_indices/definitions/{symbol}.json"
+        r = requests.get(url, timeout=10)
+
+        if r.status_code != 200:
+            raise requests.HTTPError(r.status_code)
+
+        r_json = r.json()["constituents"]
+
+        return [r_json[i]["constituent_symbol"] for i in range(0, len(r_json))]
diff --git a/openbb_sdk/providers/cboe/poetry.lock b/openbb_sdk/providers/cboe/poetry.lock
index bbdeb006281..c492fe2bfcd 100644
--- a/openbb_sdk/providers/cboe/poetry.lock
+++ b/openbb_sdk/providers/cboe/poetry.lock
@@ -541,37 +541,14 @@ files = [
 ]
 
 [[package]]
-name = "pandas"
-version = "2.0.3"
-description = "Powerful data structures for data analysis, time series, and statistics"
+name = "platformdirs"
+version = "3.10.0"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 files = [
-    {file = "pandas-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e4c7c9f27a4185304c7caf96dc7d91bc60bc162221152de697c98eb0b2648dd8"},
-    {file = "pandas-2.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f167beed68918d62bffb6ec64f2e1d8a7d297a038f86d4aed056b9493fca407f"},
-    {file = "pandas-2.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ce0c6f76a0f1ba361551f3e6dceaff06bde7514a374aa43e33b588ec10420183"},
-    {file = "pandas-2.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba619e410a21d8c387a1ea6e8a0e49bb42216474436245718d7f2e88a2f8d7c0"},
-    {file = "pandas-2.0.3-cp310-cp310-win32.whl", hash = "sha256:3ef285093b4fe5058eefd756100a367f27029913760773c8bf1d2d8bebe5d210"},
-    {file = "pandas-2.0.3-cp310-cp310-win_amd64.whl", hash = "sha256:9ee1a69328d5c36c98d8e74db06f4ad518a1840e8ccb94a4ba86920986bb617e"},
-    {file = "pandas-2.0.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b084b91d8d66ab19f5bb3256cbd5ea661848338301940e17f4492b2ce0801fe8"},
-    {file = "pandas-2.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:37673e3bdf1551b95bf5d4ce372b37770f9529743d2498032439371fc7b7eb26"},
-    {file = "pandas-2.0.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b9cb1e14fdb546396b7e1b923ffaeeac24e4cedd14266c3497216dd4448e4f2d"},
-    {file = "pandas-2.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d9cd88488cceb7635aebb84809d087468eb33551097d600c6dad13602029c2df"},
-    {file = "pandas-2.0.3-cp311-cp311-win32.whl", hash = "sha256:694888a81198786f0e164ee3a581df7d505024fbb1f15202fc7db88a71d84ebd"},
-    {file = "pandas-2.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:6a21ab5c89dcbd57f78d0ae16630b090eec626360085a4148693def5452d8a6b"},
-    {file = "pandas-2.0.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:9e4da0d45e7f34c069fe4d522359df7d23badf83abc1d1cef398895822d11061"},
-    {file = "pandas-2.0.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:32fca2ee1b0d93dd71d979726b12b61faa06aeb93cf77468776287f41ff8fdc5"},
-    {file = "pandas-2.0.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:258d3624b3ae734490e4d63c430256e716f488c4fcb7c8e9bde2d3aa46c29089"},
-    {file = "pandas-2.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eae3dc34fa1aa7772dd3fc60270d13ced7346fcbcfee017d3132ec625e23bb0"},
-    {file = "pandas-2.0.3-cp38-cp38-win32.whl", hash = "sha256:f3421a7afb1a43f7e38e82e844e2bca9a6d793d66c1a7f9f0ff39a795bbc5e02"},
-    {file = "pandas-2.0.3-cp38-cp38-win_amd64.whl", hash = "sha256:69d7f3884c95da3a31ef82b7618af5710dba95bb885ffab339aad925c3e8ce78"},
-    {file = "pandas-2.0.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5247fb1ba347c1261cbbf0fcfba4a3121fbb4029d95d9ef4dc45406620b25c8b"},
-    {file = "pandas-2.0.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:81af086f4543c9d8bb128328b5d32e9986e0c84d3ee673a2ac6fb57fd14f755e"},
-    {file = "pandas-2.0.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1994c789bf12a7c5098277fb43836ce090f1073858c10f9220998ac74f37c69b"},
-    {file = "pandas-2.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ec591c48e29226bcbb316e0c1e9423622bc7a4eaf1ef7c3c9fa1a3981f89641"},
-    {file = "pandas-2.0.3-cp39-cp39-win32.whl", hash = "sha256:04dbdbaf2e4d46ca8da896e1805bc04eb85caa9a82e259e8eed00254d5e0c682"},
-    {file = "pandas-2.0.3-cp39-cp39-win_amd64.whl", hash = "sha256:1168574b036cd8b93abc746171c9b4f1b83467438a5e45909fed645cf8692dbc"},
-    {file = "pandas-2.0.3.tar.gz", hash = "sha256:c02f372a88e0d17f36d3093a644c73cfc1788e876a7c4bcb4020a77512e2043c"},
+    {file = "platformdirs-3.10.0-py3-none-any.whl", hash = "sha256:d7c24979f292f916dc9cbf8648319032f551ea8c49a4c9bf2fb556a02070ec1d"},
+    {file = "platformdirs-3.10.0.tar.gz", hash = "sha256:b45696dab2d7cc691a3226759c0d3b00c47c8b6e293d96f6436f733303f77f6d"},
 ]
 
 [package.dependencies]
@@ -965,14 +942,14 @@ files = [
 ]
 
 [[package]]
-name = "tzdata"
-version = "2023.3"
-description = "Provider of IANA time zone data"
+name = "url-normalize"
+version = "1.4.3"
+description = "URL normalization for Python"
 optional = false
-python-versions = ">=2"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
-    {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
+    {file = "url-normalize-1.4.3.tar.gz", hash = "sha256:d23d3a070ac52a67b83a1c59a0e68f8608d1cd538783b401bc9de2c0fac999b2"},
+    {file = "url_normalize-1.4.3-py2.py3-none-any.whl", hash = "sha256:ec3c301f04e5bb676d333a7fa162fa977ad2ca04b7e652bfc9fac4e405728eed"},
 ]
 
 [[package]]
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/__init__.py b/openbb_sdk/providers/fmp/openbb_fmp/__init__.py
index 8329e778b87..deab8f902b4 100644
--- a/openbb_sdk/providers/fmp/openbb_fmp/__init__.py
+++ b/openbb_sdk/providers/fmp/openbb_fmp/__init__.py
@@ -8,13 +8,13 @@ from openbb_fmp.models.balance_sheet_growth import FMPBalanceSheetGrowthFetcher
 from openbb_fmp.models.cash_flow import FMPCashFlowStatementFetcher
 from openbb_fmp.models.cash_flow_growth import FMPCashFlowStatementGrowthFetcher
 from openbb_fmp.models.company_overview import FMPCompanyOverviewFetcher
-from openbb_fmp.models.crypto_eod import FMPCryptoEODFetcher
+from openbb_fmp.models.crypto_historical import FMPCryptoHistoricalFetcher
 from openbb_fmp.models.dividend_calendar import FMPDividendCalendarFetcher
 from openbb_fmp.models.earnings_calendar import FMPEarningsCalendarFetcher
 from openbb_fmp.models.earnings_call_transcript import FMPEarningsCallTranscriptFetcher
 from openbb_fmp.models.executive_compensation import FMPExecutiveCompensationFetcher
 from openbb_fmp.models.financial_ratios import FMPFinancialRatiosFetcher
-from openbb_fmp.models.forex_eod import FMPForexEODFetcher
+from openbb_fmp.models.forex_historical import FMPForexHistoricalFetcher
 from openbb_fmp.models.forex_pairs import FMPForexPairsFetcher
 from openbb_fmp.models.global_news import FMPGlobalNewsFetcher
 from openbb_fmp.models.historical_dividends import FMPHistoricalDividendsFetcher
@@ -28,7 +28,7 @@ from openbb_fmp.models.key_metrics import FMPKeyMetricsFetcher
 from openbb_fmp.models.major_indices_constituents import (
     FMPMajorIndicesConstituentsFetcher,
 )
-from openbb_fmp.models.major_indices_eod import FMPMajorIndicesEODFetcher
+from openbb_fmp.models.major_indices_historical import FMPMajorIndicesHistoricalFetcher
 from openbb_fmp.models.price_target import FMPPriceTargetFetcher
 from openbb_fmp.models.price_target_consensus import FMPPriceTargetConsensusFetcher
 from openbb_fmp.models.revenue_business_line import FMPRevenueBusinessLineFetcher
@@ -36,7 +36,7 @@ from openbb_fmp.models.revenue_geographic import FMPRevenueGeographicFetcher
 from openbb_fmp.models.risk_premium import FMPRiskPremiumFetcher
 from openbb_fmp.models.sec_filings import FMPSECFilingsFetcher
 from openbb_fmp.models.share_statistics import FMPShareStatisticsFetcher
-from openbb_fmp.models.stock_eod import FMPStockEODFetcher
+from openbb_fmp.models.stock_historical import FMPStockHistoricalFetcher
 from openbb_fmp.models.stock_insider_trading import FMPStockInsiderTradingFetcher
 from openbb_fmp.models.stock_multiples import FMPStockMultiplesFetcher
 from openbb_fmp.models.stock_news import FMPStockNewsFetcher
@@ -54,7 +54,7 @@ fmp_provider = Provider(
     required_credentials=["api_key"],
     fetcher_dict={
         "KeyExecutives": FMPKeyExecutivesFetcher,
-        "StockEOD": FMPStockEODFetcher,
+        "StockHistorical": FMPStockHistoricalFetcher,
         "GlobalNews": FMPGlobalNewsFetcher,
         "StockNews": FMPStockNewsFetcher,
         "IncomeStatement": FMPIncomeStatementFetcher,
@@ -64,7 +64,7 @@ fmp_provider = Provider(
         "CashFlowStatement": FMPCashFlowStatementFetcher,
         "CashFlowStatementGrowth": FMPCashFlowStatementGrowthFetcher,
         "ShareStatistics": FMPShareStatisticsFetcher,
-        "MajorIndicesEOD": FMPMajorIndicesEODFetcher,
+        "MajorIndicesHistorical": FMPMajorIndicesHistoricalFetcher,
         "RevenueGeographic": FMPRevenueGeographicFetcher,
         "RevenueBusinessLine": FMPRevenueBusinessLineFetcher,
         "InstitutionalOwnership": FMPInstitutionalOwnershipFetcher,
@@ -83,8 +83,8 @@ fmp_provider = Provider(
         "SECFilings": FMPSECFilingsFetcher,
         "TreasuryRates": FMPTreasuryRatesFetcher,
         "ExecutiveCompensation": FMPExecutiveCompensationFetcher,
-        "CryptoEOD": FMPCryptoEODFetcher,
-        "ForexEOD": FMPForexEODFetcher,
+        "CryptoHistorical": FMPCryptoHistoricalFetcher,
+        "ForexHistorical": FMPForexHistoricalFetcher,
         "ForexPairs": FMPForexPairsFetcher,
         "StockPeers": FMPStockPeersFetcher,
         "StockMultiples": FMPStockMultiplesFetcher,
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/available_indices.py b/openbb_sdk/providers/fmp/openbb_fmp/models/available_indices.py
index 340559b8d66..b8cc90e9afd 100644
--- a/openbb_sdk/providers/fmp/openbb_fmp/models/available_indices.py
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/available_indices.py
@@ -8,6 +8,7 @@ from openbb_provider.standard_models.available_indices import (
     AvailableIndicesData,
     AvailableIndicesQueryParams,
 )
+from pydantic import Field
 
 from openbb_fmp.utils.helpers import get_data_many
 
@@ -22,6 +23,22 @@ class FMPAvailableIndicesQueryParams(AvailableIndicesQueryParams):
 class FMPAvailableIndicesData(AvailableIndicesData):
     """FMP Available Indices Data."""
 
+    class Config:
+        """Pydantic alias config using fields Dict."""
+
+        fields = {
+            "stock_exchange": "stockExchange",
+            "exchange_short_name": "exchangeShortName",
+        }
+
+    stock_exchange: str = Field(
+        description="Stock exchange where the index is listed.", alias="stockExchange"
+    )
+    exchange_short_name: str = Field(
+        description="Short name of the stock exchange where the index is listed.",
+        alias="exchangeShortName",
+    )
+
 
 class FMPAvailableIndicesFetcher(
     Fetcher[
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/balance_sheet.py b/openbb_sdk/providers/fmp/openbb_fmp/models/balance_sheet.py
index 4b615c7bedb..5ca1409a3cc 100644
--- a/openbb_sdk/providers/fmp/openbb_fmp/models/balance_sheet.py
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/balance_sheet.py
@@ -1,6 +1,10 @@
 """FMP Balance Sheet Fetcher."""
 
 
+from datetime import (
+    date as dateType,
+    datetime,
+)
 from typing import Any, Dict, List, Optional
 
 from openbb_provider.abstract.fetcher import Fetcher
@@ -8,7 +12,7 @@ from openbb_provider.standard_models.balance_sheet import (
     BalanceSheetData,
     BalanceSheetQueryParams,
 )
-from pydantic import root_validator
+from pydantic import Field, validator
 
 from openbb_fmp.utils.helpers import create_url, get_data_many
 
@@ -19,14 +23,7 @@ class FMPBalanceSheetQueryParams(BalanceSheetQueryParams):
     Source: https://financialmodelingprep.com/developer/docs/#Balance-Sheet
     """
 
-    cik: Optional[str]
-
-    @root_validator()
-    def check_symbol_or_cik(cls, values):  # pylint: disable=no-self-argument
-        """Check if symbol or cik is provided."""
-        if values.get("symbol") is None and values.get("cik") is None:
-            raise ValueError("symbol or cik must be provided")
-        return values
+    symbol: str = Field(description="Symbol/CIK of the company.")
 
 
 class FMPBalanceSheetData(BalanceSheetData):
@@ -36,31 +33,43 @@ class FMPBalanceSheetData(BalanceSheetData):
         """Pydantic alias config using fields Dict."""
 
         fields = {
-            "currency": "reportedCurrency",
-            "current_assets": "totalCurrentAssets",
-            "noncurrent_assets": "totalNonCurrentAssets",
-            "assets": "totalAssets",
-            "current_liabilities": "totalCurrentLiabilities",
-            "noncurrent_liabilities": "totalNonCurrentLiabilities",
-            "liabilities": "totalLiabilities",
-            "other_stockholder_equity": "othertotalStockholdersEquity",
+            "marketable_securities": "longTermInvestments",
+            "other_shareholder_equity": "othertotalStockholdersEquity",
+            "total_shareholder_equity": "totalStockholdersEquity",
+            "total_liabilities_and_shareholders_equity": "totalLiabilitiesAndStockholdersEquity",
         }
 
-    # Leftovers below
-    calendarYear: Optional[int]
-    link: Optional[str]
-    finalLink: Optional[str]
+    reported_currency: str = Field(description="Reported currency in the statement.")
 
-    cashAndShortTermInvestments: Optional[int]
-    goodwillAndIntangibleAssets: Optional[int]
-    deferredRevenueNonCurrent: Optional[int]
-    totalInvestments: Optional[int]
+    filling_date: dateType = Field(description="Filling date.")
+    accepted_date: datetime = Field(description="Accepted date.")
+    calendar_year: int = Field(description="Calendar year.")
 
-    capitalLeaseObligations: Optional[int]
-    deferredTaxLiabilitiesNonCurrent: Optional[int]
-    totalNonCurrentLiabilities: Optional[int]
-    totalDebt: Optional[int]
-    netDebt: Optional[int]
+    cash_and_short_term_investments: Optional[int] = Field(
+        description="Cash and short term investments"
+    )
+    goodwill_and_intangible_assets: Optional[int] = Field(
+        description="Goodwill and Intangible Assets"
+    )
+    capital_lease_obligations: Optional[int] = Field(
+        description="Capital lease obligations"
+    )
+    total_investments: Optional[int] = Field(description="Total investments")
+    total_debt: Optional[int] = Field(description="Total debt")
+    net_debt: Optional[int] = Field(description="Net debt")
+
+    link: str = Field(description="Link to the statement.")
+    final_link: str = Field(description="Link to the final statement.")
+
+    @validator("filing_date", pre=True, check_fields=False)
+    def filing_date_validate(cls, v):  # pylint: disable=no-self-argument
+        """Validate the filing date."""
+        return datetime.strptime(v, "%Y-%m-%d").date()
+
+    @validator("accepted_date", pre=True, check_fields=False)
+    def accepted_date_validate(cls, v):  # pylint: disable=no-self-argument
+        """Validate the accepted date."""
+        return datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
 
 
 class FMPBalanceSheetFetcher(
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/cash_flow.py b/openbb_sdk/providers/fmp/openbb_fmp/models/cash_flow.py
index d70bfdde0f4..8b309aeb91f 100644
--- a/openbb_sdk/providers/fmp/openbb_fmp/models/cash_flow.py
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/cash_flow.py
@@ -1,14 +1,18 @@
 """FMP Cash Flow Statement Fetcher."""
 
 
+from datetime import (
+    date as dateType,
+    datetime,
+)
 from typing import Any, Dict, List, Optional
 
 from openbb_provider.abstract.fetcher import Fetcher
-from openbb_provider.standard_models.cash_flows import (
+from openbb_provider.standard_models.cash_flow import (
     CashFlowStatementData,
     CashFlowStatementQueryParams,
 )
-from pydantic import Field, root_validator
+from pydantic import Field, validator
 
 from openbb_fmp.utils.helpers import create_url, get_data_many
 
@@ -19,14 +23,7 @@ class FMPCashFlowStatementQueryParams(CashFlowStatementQueryParams):
     Source: https://financialmodelingprep.com/developer/docs/#Cash-Flow-Statement
     """
 
-    cik: Optional[str] = Field(description="Central Index Key (CIK) of the company.")
-
-    @root_validator()
-    def check_symbol_or_cik(cls, values):  # pylint: disable=no-self-argument
-        """Validate that either a symbol or CIK is provided."""
-        if values.get("symbol") is None and values.get("cik") is None:
-            raise ValueError("symbol or cik must be provided")
-        return values
+    symbol: str = Field(description="Symbol/CIK of the company.")
 
 
 class FMPCashFlowStatementData(CashFlowStatementData):
@@ -36,20 +33,52 @@ class FMPCashFlowStatementData(CashFlowStatementData):
         """Pydantic alias config using fields dict."""
 
         fields = {
-            "currency": "reportedCurrency",
             "net_cash_flow_from_operating_activities": "netCashProvidedByOperatingActivities",
+            "purchases_of_marketable_securities": "purchasesOfInvestments",
+            "sales_from_maturities_of_investments": "salesMaturitiesOfInvestments",
+            "payments_from_acquisitions": "acquisitionsNet",
             "other_investing_activities": "otherInvestingActivites",
-            "net_cash_used_for_investing_activities": "netCashUsedForInvestingActivites",
+            "net_cash_flow_from_investing_activities": "netCashUsedForInvestingActivites",
             "other_financing_activities": "otherFinancingActivites",
             "net_cash_flow_from_financing_activities": "netCashUsedProvidedByFinancingActivities",
         }
 
-    # Leftovers below
-    calendar_year: Optional[int] = Field(
-        description="Calendar Year", alias="calendarYear"
+    reported_currency: str = Field(description="Reported currency in the statement.")
+    filling_date: dateType = Field(description="Filling date.")
+    accepted_date: datetime = Field(description="Accepted date.")
+    calendar_year: int = Field(description="Calendar year.")
+
+    change_in_working_capital: Optional[int] = Field(
+        description="Change in working capital."
     )
-    link: Optional[str]
-    final_link: Optional[str] = Field(description="Final Link", alias="finalLink")
+    other_working_capital: Optional[int] = Field(description="Other working capital.")
+    common_stock_issued: Optional[int] = Field(description="Common stock issued.")
+    effect_of_forex_changes_on_cash: Optional[int] = Field(
+        description="Effect of forex changes on cash."
+    )
+
+    cash_at_beginning_of_period: Optional[int] = Field(
+        description="Cash at beginning of period."
+    )
+    cash_at_end_of_period: Optional[int] = Field(
+        description="Cash, cash equivalents, and restricted cash at end of period"
+    )
+    operating_cash_flow: Optional[int] = Field(description="Operating cash flow.")
+    capital_expenditure: Optional[int] = Field(description="Capital expenditure.")
+    free_cash_flow: Optional[int] = Field(description="Free cash flow.")
+
+    link: str = Field(description="Link to the statement.")
+    final_link: str = Field(description="Link to the final statement.")
+
+    @validator("filing_date", pre=True, check_fields=False)
+    def filing_date_validate(cls, v):  # pylint: disable=no-self-argument
+        """Validate the filing date."""
+        return datetime.strptime(v, "%Y-%m-%d").date()
+
+    @validator("accepted_date", pre=True, check_fields=False)
+    def accepted_date_validate(cls, v):  # pylint: disable=no-self-argument
+        """Validate the accepted date."""
+        return datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
 
 
 class FMPCashFlowStatementFetcher(
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/crypto_historical.py b/openbb_sdk/providers/fmp/openbb_fmp/models/crypto_historical.py
new file mode 100644
index 00000000000..9662c743e75
--- /dev/null
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/crypto_historical.py
@@ -0,0 +1,100 @@
+"""FMP Cryptos end of day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.crypto_historical import (
+    CryptoHistoricalData,
+    CryptoHistoricalQueryParams,
+)
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, NonNegativeInt, validator
+
+from openbb_fmp.utils.helpers import get_data_many
+
+
+class FMPCryptoHistoricalQueryParams(CryptoHistoricalQueryParams):
+    # noqa: E501
+    """FMP Crypto end of day Query.
+
+    Source:
+    https://site.financialmodelingprep.com/developer/docs/cryptocurrency-historical-data-api/#Historical-Daily-Prices
+    """
+
+    timeseries: Optional[NonNegativeInt] = Field(
+        default=None, description="Number of days to look back."
+    )
+
+
+class FMPCryptoHistoricalData(CryptoHistoricalData):
+    """FMP Crypto end of day Data."""
+
+    adjClose: float = Field(
+        description="Adjusted Close Price of the symbol.", alias="adj_close"
+    )
+    unadjustedVolume: float = Field(
+        description="Unadjusted volume of the symbol.", alias="unadjusted_volume"
+    )
+    change: float = Field(
+        description="Change in the price of the symbol from the previous day.",
+        alias="change",
+    )
+    changePercent: float = Field(
+        description=r"Change \% in the price of the symbol.", alias="change_percent"
+    )
+    label: str = Field(description="Human readable format of the date.")
+    changeOverTime: float = Field(
+        description=r"Change \% in the price of the symbol over a period of time.",
+        alias="change_over_time",
+    )
+
+    @validator("date", pre=True)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return datetime.strptime(v, "%Y-%m-%d")
+
+
+class FMPCryptoHistoricalFetcher(
+    Fetcher[
+        FMPCryptoHistoricalQueryParams,
+        List[FMPCryptoHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the FMP endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> FMPCryptoHistoricalQueryParams:
+        """Transform the query params. Start and end dates are set to 1 year interval."""
+        transformed_params = params
+
+        now = datetime.now().date()
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+        return FMPCryptoHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: FMPCryptoHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the FMP endpoint."""
+        api_key = credentials.get("fmp_api_key") if credentials else ""
+
+        base_url = "https://financialmodelingprep.com/api/v3/"
+        query_str = get_querystring(query.dict(by_alias=True), ["symbol"])
+        query_str = query_str.replace("start_date", "from").replace("end_date", "to")
+        url = f"{base_url}historical-price-full/crypto/{query.symbol}?{query_str}&apikey={api_key}"
+
+        return get_data_many(url, "historical", **kwargs)
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[FMPCryptoHistoricalData]:
+        """Return the transformed data."""
+        return [FMPCryptoHistoricalData(**d) for d in data]
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/forex_historical.py b/openbb_sdk/providers/fmp/openbb_fmp/models/forex_historical.py
new file mode 100644
index 00000000000..dc9224b944c
--- /dev/null
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/forex_historical.py
@@ -0,0 +1,94 @@
+"""FMP Forex end of day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.forex_historical import (
+    ForexHistoricalData,
+    ForexHistoricalQueryParams,
+)
+from pydantic import Field, validator
+
+from openbb_fmp.utils.helpers import get_data_many, get_querystring
+
+
+class FMPForexHistoricalQueryParams(ForexHistoricalQueryParams):
+    """FMP Forex end of day Query.
+
+    Source: https://site.financialmodelingprep.com/developer/docs/#Historical-Forex-Price
+    """
+
+
+class FMPForexHistoricalData(ForexHistoricalData):
+    """FMP Forex end of day Data."""
+
+    adjClose: float = Field(
+        description="Adjusted Close Price of the symbol.", alias="adj_close"
+    )
+    unadjustedVolume: float = Field(
+        description="Unadjusted volume of the symbol.", alias="unadjusted_volume"
+    )
+    change: float = Field(
+        description="Change in the price of the symbol from the previous day.",
+        alias="change",
+    )
+    changePercent: float = Field(
+        description=r"Change \% in the price of the symbol.", alias="change_percent"
+    )
+    label: str = Field(description="Human readable format of the date.")
+    changeOverTime: float = Field(
+        description=r"Change \% in the price of the symbol over a period of time.",
+        alias="change_over_time",
+    )
+
+    @validator("date", pre=True)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return datetime.strptime(v, "%Y-%m-%d")
+
+
+class FMPForexHistoricalFetcher(
+    Fetcher[
+        FMPForexHistoricalQueryParams,
+        List[FMPForexHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the FMP endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> FMPForexHistoricalQueryParams:
+        """Transform the query params. Start and end dates are set to a 1 year interval."""
+        transformed_params = params
+
+        now = datetime.now().date()
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+
+        return FMPForexHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: FMPForexHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the FMP endpoint."""
+        api_key = credentials.get("fmp_api_key") if credentials else ""
+
+        base_url = "https://financialmodelingprep.com/api/v3"
+        query_str = get_querystring(query.dict(by_alias=True), ["symbol"])
+        query_str = query_str.replace("start_date", "from").replace("end_date", "to")
+        url = f"{base_url}/historical-price-full/forex/{query.symbol}?{query_str}&apikey={api_key}"
+
+        return get_data_many(url, "historical", **kwargs)
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[FMPForexHistoricalData]:
+        """Return the transformed data."""
+        return [FMPForexHistoricalData(**d) for d in data]
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/income_statement.py b/openbb_sdk/providers/fmp/openbb_fmp/models/income_statement.py
index a3a5f600fa9..f6d7952bdb4 100644
--- a/openbb_sdk/providers/fmp/openbb_fmp/models/income_statement.py
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/income_statement.py
@@ -1,6 +1,10 @@
 """FMP Income Statement Fetcher."""
 
 
+from datetime import (
+    date as dateType,
+    datetime,
+)
 from typing import Any, Dict, List, Literal, Optional
 
 from openbb_provider.abstract.fetcher import Fetcher
@@ -19,13 +23,9 @@ class FMPIncomeStatementQueryParams(IncomeStatementQueryParams):
     """FMP Income Statement QueryParams.
 
     Source: https://financialmodelingprep.com/developer/docs/#Income-Statement
-
-    Either a Symbol or CIK is required. Symbol is preferred over CIK.
     """
 
-    cik: Optional[str] = Field(
-        description="The CIK of the company if no symbol is provided."
-    )
+    symbol: str = Field(description="Symbol/CIK of the company.")
 
     @root_validator()
     def check_symbol_or_cik(cls, values):  # pylint: disable=no-self-argument
@@ -42,13 +42,82 @@ class FMPIncomeStatementData(IncomeStatementData):
         """Pydantic alias config using fields dict."""
 
         fields = {
-            "currency": "reportedCurrency",
+            "cost_of_revenue": "costOfRevenue",
+            "gross_profit": "grossProfit",
+            "gross_profit_ratio": "grossProfitRatio",
+            "research_and_development_expenses": "researchAndDevelopmentExpenses",
+            "general_and_administrative_expenses": "generalAndAdministrativeExpenses",
+            "selling_and_marketing_expenses": "sellingAndMarketingExpenses",
+            "selling_general_and_administrative_expenses": "sellingGeneralAndAdministrativeExpenses",
+            "other_expenses": "otherExpenses",
+            "operating_expenses": "operatingExpenses",
+            "depreciation_and_amortization": "depreciationAndAmortization",
             "ebitda_ratio": "ebitdaratio",
+            "operating_income": "operatingIncome",
+            "operating_income_ratio": "operatingIncomeRatio",
+            "interest_income": "interestIncome",
+            "interest_expense": "interestExpense",
+            "total_other_income_expenses_net": "totalOtherIncomeExpensesNet",
+            "income_before_tax": "incomeBeforeTax",
+            "income_before_tax_ratio": "incomeBeforeTaxRatio",
+            "income_tax_expense": "incomeTaxExpense",
+            "net_income": "netIncome",
+            "net_income_ratio": "netIncomeRatio",
             "eps_diluted": "epsdiluted",
             "weighted_average_shares_outstanding": "weightedAverageShsOut",
             "weighted_average_shares_outstanding_dil": "weightedAverageShsOutDil",
         }
 
+        reported_currency: Optional[str] = Field(description="Reporting currency.")
+        filing_date: Optional[dateType] = Field(description="Filling date.")
+        accepted_date: Optional[datetime] = Field(description="Accepted date.")
+        calendar_year: Optional[int] = Field(description="Calendar year.")
+
+        cost_of_revenue: Optional[float] = Field(description="Cost of revenue.")
+        gross_profit: Optional[float] = Field(description="Gross profit.")
+        gross_profit_ratio: Optional[float] = Field(description="Gross profit ratio.")
+        research_and_development_expenses: Optional[float] = Field(
+            description="Research and development expenses."
+        )
+        general_and_administrative_expenses: Optional[float] = Field(
+            description="General and administrative expenses."
+        )
+        selling_and_marketing_expenses: Optional[float] = Field(
+            description="Selling and marketing expenses."
+        )
+        selling_general_and_administrative_expenses: Optional[float] = Field(
+            description="Selling, general and administrative expenses."
+        )
+        other_expenses: Optional[float] = Field(description="Other expenses.")
+
+        operating_expenses: Optional[float] = Field(description="Operating expenses.")
+        depreciation_and_amortization: Optional[float] = Field(
+            description="Depreciation and amortization."
+        )
+        ebitda_ratio: Optional[float] = Field(description="EBIDTA ratio.")
+        operating_income: Optional[float] = Field(description="Operating income.")
+        operating_income_ratio: Optional[float] = Field(
+            description="Operating income ratio."
+        )
+        interest_income: Optional[float] = Field(description="Interest income.")
+        interest_expense: Optional[float] = Field(description="Interest expense.")
+
+        total_other_income_expenses_net: Optional[float] = Field(
+            description="Total other income expenses net."
+        )
+        income_before_tax: Optional[float] = Field(description="Income before tax.")
+        income_before_tax_ratio: Optional[float] = Field(
+            description="Income before tax ratio."
+        )
+        income_tax_expense: Optional[float] = Field(description="Income tax expense.")
+        net_income: Optional[float] = Field(description="Net income.")
+        net_income_ratio: Optional[float] = Field(description="Net income ratio.")
+
+        link: Optional[str] = Field(description="Link to the income statement.")
+        final_link: Optional[str] = Field(
+            description="Final link to the income statement."
+        )
+
 
 class FMPIncomeStatementFetcher(
     Fetcher[
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/major_indices_historical.py b/openbb_sdk/providers/fmp/openbb_fmp/models/major_indices_historical.py
new file mode 100644
index 00000000000..d367f166c8a
--- /dev/null
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/major_indices_historical.py
@@ -0,0 +1,108 @@
+"""FMP Major Indices end of day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.major_indices_historical import (
+    MajorIndicesHistoricalData,
+    MajorIndicesHistoricalQueryParams,
+)
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, NonNegativeInt, validator
+
+from openbb_fmp.utils.helpers import get_data_many
+
+
+class FMPMajorIndicesHistoricalQueryParams(MajorIndicesHistoricalQueryParams):
+    """FMP Major Indices end of day Query.
+
+    Source: https://site.financialmodelingprep.com/developer/docs/historical-index-price-api/
+    """
+
+    timeseries: Optional[NonNegativeInt] = Field(
+        default=None, description="Number of days to look back."
+    )
+    interval: Literal[
+        "1min", "5min", "15min", "30min", "1hour", "4hour", "1day"
+    ] = Field(default="1day", description="Interval of the data to fetch.")
+
+
+class FMPMajorIndicesHistoricalData(MajorIndicesHistoricalData):
+    """FMP Major Indices end of day Data."""
+
+    adj_close: Optional[float] = Field(
+        description="Adjusted Close Price of the symbol.",
+        default=None,
+    )
+    unadjusted_volume: Optional[float] = Field(
+        description="Unadjusted volume of the symbol.",
+        default=None,
+    )
+    change: Optional[float] = Field(
+        description="Change in the price of the symbol from the previous day.",
+        default=None,
+    )
+    change_percent: Optional[float] = Field(
+        description=r"Change \% in the price of the symbol.",
+        default=None,
+    )
+    label: Optional[str] = Field(
+        description="Human readable format of the date.", default=None
+    )
+    change_over_time: Optional[float] = Field(
+        description=r"Change \% in the price of the symbol over a period of time.",
+        default=None,
+    )
+
+    @validator("date", pre=True)
+    def date_validate(cls, v) -> datetime:  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        # TODO: Check if this condition is necessary
+        # if values.get("changeOverTime", None) is not None:
+        #     return datetime.strptime(v, "%Y-%m-%d")
+        return datetime.strptime(v, "%Y-%m-%d")
+
+
+class FMPMajorIndicesHistoricalFetcher(
+    Fetcher[
+        FMPMajorIndicesHistoricalQueryParams,
+        List[FMPMajorIndicesHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the FMP endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> FMPMajorIndicesHistoricalQueryParams:
+        """Transform the query params."""
+        return FMPMajorIndicesHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: FMPMajorIndicesHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the FMP endpoint."""
+        api_key = credentials.get("fmp_api_key") if credentials else ""
+
+        base_url = "https://financialmodelingprep.com/api/v3"
+        query_str = (
+            get_querystring(query.dict(), ["symbol"])
+            .replace("start_date", "from")
+            .replace("end_date", "to")
+        )
+
+        url_params = f"{query.symbol}?{query_str}&apikey={api_key}"
+        url = f"{base_url}/historical-chart/{query.interval}/%5E{url_params}"
+
+        if query.interval == "1day":
+            url = f"{base_url}/historical-price-full/index/%5E{url_params}"
+
+        return get_data_many(url, "historical", **kwargs)
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[FMPMajorIndicesHistoricalData]:
+        """Return the transformed data."""
+        return [FMPMajorIndicesHistoricalData(**d) for d in data]
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/stock_historical.py b/openbb_sdk/providers/fmp/openbb_fmp/models/stock_historical.py
new file mode 100644
index 00000000000..0191c0c2c23
--- /dev/null
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/stock_historical.py
@@ -0,0 +1,111 @@
+"""FMP Stocks end of day fetcher."""
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_historical import (
+    StockHistoricalData,
+    StockHistoricalQueryParams,
+)
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, NonNegativeInt, validator
+
+from openbb_fmp.utils.helpers import get_data_many
+
+
+class FMPStockHistoricalQueryParams(StockHistoricalQueryParams):
+    """FMP Stock end of day Query.
+
+    Source: https://financialmodelingprep.com/developer/docs/#Stock-Historical-Price
+    """
+
+    timeseries: Optional[NonNegativeInt] = Field(
+        default=None, description="Number of days to look back."
+    )
+    interval: Literal[
+        "1min", "5min", "15min", "30min", "1hour", "4hour", "1day"
+    ] = Field(default="1day", description="Interval of the data to fetch.")
+
+
+class FMPStockHistoricalData(StockHistoricalData):
+    """FMP Stock end of day Data."""
+
+    adjClose: Optional[float] = Field(description="Adjusted Close Price of the symbol.")
+    unadjustedVolume: Optional[float] = Field(
+        description="Unadjusted volume of the symbol."
+    )
+    change: Optional[float] = Field(
+        description="Change in the price of the symbol from the previous day."
+    )
+    changePercent: Optional[float] = Field(
+        description=r"Change \% in the price of the symbol."
+    )
+    vwap: Optional[float] = Field(
+        description="Volume Weighted Average Price of the symbol."
+    )
+    label: Optional[str] = Field(description="Human readable format of the date.")
+    changeOverTime: Optional[float] = Field(
+        description=r"Change \% in the price of the symbol over a period of time."
+    )
+
+    @validator("date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        try:
+            return datetime.strptime(v, "%Y-%m-%d %H:%M:%S")
+        except ValueError:
+            return datetime.strptime(v, "%Y-%m-%d")
+
+
+class FMPStockHistoricalFetcher(
+    Fetcher[
+        FMPStockHistoricalQueryParams,
+        List[FMPStockHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the FMP endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> FMPStockHistoricalQueryParams:
+        """Transform the query params."""
+        transformed_params = params
+
+        now = datetime.now().date()
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+
+        return FMPStockHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: FMPStockHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the FMP endpoint."""
+        api_key = credentials.get("fmp_api_key") if credentials else ""
+
+        base_url = "https://financialmodelingprep.com/api/v3"
+        query_str = (
+            get_querystring(query.dict(), ["symbol"])
+            .replace("start_date", "from")
+            .replace("end_date", "to")
+        )
+
+        url_params = f"{query.symbol}?{query_str}&apikey={api_key}"
+        url = f"{base_url}/historical-chart/{query.interval}/{url_params}"
+
+        if query.interval == "1day":
+            url = f"{base_url}/historical-price-full/{url_params}"
+
+        return get_data_many(url, "historical", **kwargs)
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[FMPStockHistoricalData]:
+        """Return the transformed data."""
+        return [FMPStockHistoricalData(**d) for d in data]
diff --git a/openbb_sdk/providers/fmp/openbb_fmp/models/stock_quote.py b/openbb_sdk/providers/fmp/openbb_fmp/models/stock_quote.py
index ef2b2d61a27..7f51022c646 100644
--- a/openbb_sdk/providers/fmp/openbb_fmp/models/stock_quote.py
+++ b/openbb_sdk/providers/fmp/openbb_fmp/models/stock_quote.py
@@ -9,7 +9,7 @@ from openbb_provider.standard_models.stock_quote import (
     StockQuoteData,
     StockQuoteQueryParams,
 )
-from pydantic import validator
+from pydantic import Field, validator
 
 from openbb_fmp.utils.helpers import get_data_many, get_querystring
 
@@ -31,6 +31,50 @@ class FMPStockQuoteData(StockQuoteData):
             "date": "timestamp",
         }
 
+    symbol: Optional[str] = Field(description="Symbol of the company.")
+    name: Optional[str] = Field(description="Name of the company.")
+    price: Optional[float] = Field(description="Current trading price of the stock.")
+    changes_percentage: Optional[float] = Field(
+        description="Change percentage of the stock price."
+    )
+    change: Optional[float] = Field(description="Change in the stock price.")
+    year_high: Optional[float] = Field(
+        description="Highest price of the stock in the last 52 weeks."
+    )
+    year_low: Optional[float] = Field(
+        description="Lowest price of the stock in the last 52 weeks."
+    )
+    market_cap: Optional[float] = Field(description="Market cap of the company.")
+    price_avg50: Optional[float] = Field(
+        description="50 days average price of the stock."
+    )
+    price_avg200: Optional[float] = Field(
+        description="200 days average price of the stock."
+    )
+    volume: Optional[int] = Field(
+        description="Volume of the stock in the current trading day."
+    )
+    avg_volume: Optional[int] = Field(
+        default=None,
+        description="Average volume of the stock in the last 10 trading days.",
+    )
+    exchange: Optional[str] = Field(description="Exchange the stock is traded on.")
+    open: Optional[float] = Field(
+        default=None,
+        description="Opening price of the stock in the current trading day.",
+    )
+    previous_close: Optional[float] = Field(
+        description="Previous closing price of the stock."
+    )
+    eps: Optional[float] = Field(description="Earnings per share of the stock.")
+    pe: Optional[float] = Field(description="Price earnings ratio of the stock.")
+    earnings_announcement: Optional[str] = Field(
+        description="Earnings announcement date of the stock."
+    )
+    shares_outstanding: Optional[int] = Field(
+        description="Number of shares outstanding of the stock."
+    )
+
     @validator("timestamp", pre=True, check_fields=False)
     def date_validate(cls, v):  # pylint: disable=E0213
         """Return the date as a datetime object."""
diff --git a/openbb_sdk/providers/intrinio/README.md b/openbb_sdk/providers/intrinio/README.md
new file mode 100644
index 00000000000..365004a7108
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/README.md
@@ -0,0 +1,11 @@
+# OpenBB Intrinio Provider
+
+This extension integrates the Intrinio data provider into the OpenBB SDK.
+
+## Installation
+
+To install the extension, run the following command in this folder:
+
+```bash
+pip install .
+```
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/__init__.py b/openbb_sdk/providers/intrinio/openbb_intrinio/__init__.py
new file mode 100644
index 00000000000..46665ba868f
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/__init__.py
@@ -0,0 +1,33 @@
+"""intrinio provider module."""
+
+
+from openbb_provider.abstract.provider import Provider
+
+from openbb_intrinio.models.balance_sheet import IntrinioBalanceSheetFetcher
+from openbb_intrinio.models.cash_flow import IntrinioCashFlowStatementFetcher
+from openbb_intrinio.models.forex_pairs import IntrinioForexPairsFetcher
+from openbb_intrinio.models.global_news import IntrinioGlobalNewsFetcher
+from openbb_intrinio.models.income_statement import IntrinioIncomeStatementFetcher
+from openbb_intrinio.models.options_chains import IntrinioOptionsChainsFetcher
+from openbb_intrinio.models.stock_historical import IntrinioStockHistoricalFetcher
+from openbb_intrinio.models.stock_news import IntrinioStockNewsFetcher
+from openbb_intrinio.models.stock_quote import IntrinioStockQuoteFetcher
+
+intrinio_provider = Provider(
+    name="intrinio",
+    website="https://intrinio.com/",
+    description="""Intrinio is a financial data platform that provides real-time and
+    historical financial market data to businesses and developers through an API.""",
+    required_credentials=["api_key"],
+    fetcher_dict={
+        "StockHistorical": IntrinioStockHistoricalFetcher,
+        "ForexPairs": IntrinioForexPairsFetcher,
+        "StockNews": IntrinioStockNewsFetcher,
+        "GlobalNews": IntrinioGlobalNewsFetcher,
+        "StockQuote": IntrinioStockQuoteFetcher,
+        "OptionsChains": IntrinioOptionsChainsFetcher,
+        "BalanceSheet": IntrinioBalanceSheetFetcher,
+        "CashFlowStatement": IntrinioCashFlowStatementFetcher,
+        "IncomeStatement": IntrinioIncomeStatementFetcher,
+    },
+)
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/__init__.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/__init__.py
new file mode 100644
index 00000000000..57cf91e5d44
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/__init__.py
@@ -0,0 +1 @@
+"""yfinance models directory."""
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/balance_sheet.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/balance_sheet.py
new file mode 100644
index 00000000000..e25582d2f0a
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/balance_sheet.py
@@ -0,0 +1,127 @@
+"""Intrinio Balance Sheet Fetcher."""
+
+
+from datetime import date
+from typing import Any, Dict, List, Literal, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.balance_sheet import (
+    BalanceSheetData,
+    BalanceSheetQueryParams,
+)
+from pydantic import Field
+
+from openbb_intrinio.utils.helpers import get_data_one
+
+
+class IntrinioBalanceSheetQueryParams(BalanceSheetQueryParams):
+    """Intrinio Balance Sheet QueryParams.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_fundamental_reported_financials_v2
+    Source: https://docs.intrinio.com/documentation/web_api/get_fundamental_standardized_financials_v2
+    """
+
+    type: Literal["reported", "standardized"] = Field(
+        default="reported", description="Type of the statement to be fetched."
+    )
+    year: Optional[int] = Field(
+        description="Year of the statement to be fetched.",
+    )
+
+
+class IntrinioBalanceSheetData(BalanceSheetData):
+    """Intrinio Balance Sheet Data."""
+
+    class Config:
+        fields = {
+            "cash_and_cash_equivalents": "cash_and_equivalents",
+            "marketable_securities": "short_term_investments",
+            "net_receivables": "note_and_lease_receivable",
+            "inventory": "inventory_net",
+            "total_non_current_assets": "total_noncurrent_assets",
+            "tax_payables": "other_taxes_payables",
+            "deferred_revenue": "current_deferred_revenue",
+            "deferred_revenue_non_current": "noncurrent_deferred_revenue",
+            "deferred_tax_liabilities_non_current": "noncurrent_deferred_and_payable_income_tax_liabilities",
+            "other_liabilities": "other_long_term_liabilities",
+            "accumulated_other_comprehensive_income_loss": "accumulated_other_comprehensive_income_loss",
+        }
+
+
+class IntrinioBalanceSheetFetcher(
+    Fetcher[
+        IntrinioBalanceSheetQueryParams,
+        List[IntrinioBalanceSheetData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioBalanceSheetQueryParams:
+        """Transform the query params."""
+        transform_params = params
+
+        if not params.get("year"):
+            transform_params["year"] = date.today().year - 1
+
+        return IntrinioBalanceSheetQueryParams(**transform_params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioBalanceSheetQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        url_params = f"{query.symbol}-balance_sheet_statement-{query.year}"
+        statement_param = f"{query.type}_financials"
+
+        data = []
+
+        if query.period == "annual":
+            url = f"{base_url}/fundamentals/{url_params}-FY/{statement_param}?api_key={api_key}"
+            data.append(get_data_one(url, **kwargs))
+
+        elif query.period == "quarter":
+            # TODO: Fix quarter range after Intrinio's response
+            for quarter in range(1, 4):
+                url = f"{base_url}/fundamentals/{url_params}-Q{quarter}/{statement_param}?api_key={api_key}"
+                data.append(get_data_one(url, **kwargs))
+
+        return data
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioBalanceSheetData]:
+        """Return the transformed data."""
+
+        transformed_data = []
+
+        for item in data:
+            sub_dict = {}
+
+            if "reported_financials" in item:
+                key = "reported_financials"
+                sub_tag = "xbrl_tag"
+            elif "standardized_financials" in item:
+                key = "standardized_financials"
+                sub_tag = "data_tag"
+
+            for sub_item in item[key]:
+                try:
+                    sub_dict[sub_item[sub_tag]["name"]] = int(
+                        sub_item[sub_tag]["factor"] + str(sub_item["value"])
+                    )
+                except (ValueError, KeyError):
+                    sub_dict[sub_item[sub_tag]["name"]] = int(sub_item["value"])
+
+            sub_dict["date"] = item["fundamental"]["end_date"]
+            sub_dict["period"] = item["fundamental"]["fiscal_period"]
+            sub_dict["cik"] = item["fundamental"]["company"]["cik"]
+            sub_dict["symbol"] = item["fundamental"]["company"]["ticker"]
+
+            transformed_data.append(IntrinioBalanceSheetData(**sub_dict))
+
+        return transformed_data
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/cash_flow.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/cash_flow.py
new file mode 100644
index 00000000000..9f3c4ee4b4f
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/cash_flow.py
@@ -0,0 +1,143 @@
+"""Intrinio Cash Flow Statement Fetcher."""
+
+
+from datetime import date
+from typing import Any, Dict, List, Literal, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.cash_flow import (
+    CashFlowStatementData,
+    CashFlowStatementQueryParams,
+)
+from pydantic import Field
+
+from openbb_intrinio.utils.helpers import get_data_one
+
+
+class IntrinioCashFlowStatementQueryParams(CashFlowStatementQueryParams):
+    """Intrinio Cash Flow Statement QueryParams.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_fundamental_reported_financials_v2
+    Source: https://docs.intrinio.com/documentation/web_api/get_fundamental_standardized_financials_v2
+    """
+
+    type: Literal["reported", "standardized"] = Field(
+        default="reported", description="Type of the statement to be fetched."
+    )
+    year: Optional[int] = Field(
+        description="Year of the statement to be fetched.",
+    )
+
+
+class IntrinioCashFlowStatementData(CashFlowStatementData):
+    """Intrinio Cash Flow Statement Data."""
+
+    class Config:
+        fields = {
+            "net_income": "NetIncomeLoss",
+            "depreciation_and_amortization": "DepreciationDepletionAndAmortization",
+            "stock_based_compensation": "ShareBasedCompensation",
+            "deferred_income_tax": "DeferredIncomeTaxExpenseBenefit",
+            "other_non_cash_items": "OtherNoncashIncomeExpense",
+            "accounts_receivables": "IncreaseDecreaseInAccountsReceivable",
+            "inventory": "IncreaseDecreaseInInventories",
+            "vendor_non_trade_receivables": "IncreaseDecreaseInOtherReceivables",
+            "other_current_and_non_current_assets": "IncreaseDecreaseInOtherOperatingAssets",
+            "accounts_payables": "IncreaseDecreaseInAccountsPayable",
+            "deferred_revenue": "IncreaseDecreaseInContractWithCustomerLiability",
+            "other_current_and_non_current_liabilities": "IncreaseDecreaseInOtherOperatingLiabilities",
+            "net_cash_flow_from_operating_activities": "NetCashProvidedByUsedInOperatingActivities",
+            "purchases_of_marketable_securities": "PaymentsToAcquireAvailableForSaleSecuritiesDebt",
+            "sales_from_maturities_of_investments": "ProceedsFromSaleOfAvailableForSaleSecuritiesDebt",
+            "investments_in_property_plant_and_equipment": "ProceedsFromMaturitiesPrepaymentsAndCallsOfAvailableForSaleSecurities",  # noqa: E501
+            "payments_from_acquisitions": "PaymentsToAcquireBusinessesNetOfCashAcquired",
+            "other_investing_activities": "PaymentsForProceedsFromOtherInvestingActivities",
+            "net_cash_flow_from_investing_activities": "NetCashProvidedByUsedInInvestingActivities",
+            "taxes_paid_on_net_share_settlement": "PaymentsRelatedToTaxWithholdingForShareBasedCompensation",
+            "dividends_paid": "PaymentsOfDividends",
+            "common_stock_repurchased": "PaymentsForRepurchaseOfCommonStock",
+            "debt_proceeds": "ProceedsFromIssuanceOfLongTermDebt",
+            "debt_repayment": "RepaymentsOfLongTermDebt",
+            "other_financing_activities": "ProceedsFromPaymentsForOtherFinancingActivities",
+            "net_cash_flow_from_financing_activities": "NetCashProvidedByUsedInFinancingActivities",
+            "net_change_in_cash": "CashCashEquivalentsRestrictedCashAndRestrictedCashEquivalentsPeriodIncreaseDecreaseIncludingExchangeRateEffect",  # noqa: E501
+        }
+
+
+class IntrinioCashFlowStatementFetcher(
+    Fetcher[
+        IntrinioCashFlowStatementQueryParams,
+        List[IntrinioCashFlowStatementData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioCashFlowStatementQueryParams:
+        """Transform the query params."""
+        transform_params = params
+
+        if not params.get("year"):
+            transform_params["year"] = date.today().year - 1
+
+        return IntrinioCashFlowStatementQueryParams(**transform_params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioCashFlowStatementQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        url_params = f"{query.symbol}-cash_flow_statement-{query.year}"
+        statement_param = f"{query.type}_financials"
+
+        data = []
+
+        if query.period == "annual":
+            url = f"{base_url}/fundamentals/{url_params}-FY/{statement_param}?api_key={api_key}"
+            data.append(get_data_one(url, **kwargs))
+
+        elif query.period == "quarter":
+            # TODO: Fix quarter range after Intrinio's response
+            for quarter in range(1, 4):
+                url = f"{base_url}/fundamentals/{url_params}-Q{quarter}/{statement_param}?api_key={api_key}"
+                data.append(get_data_one(url, **kwargs))
+
+        return data
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioCashFlowStatementData]:
+        """Return the transformed data."""
+
+        transformed_data = []
+
+        for item in data:
+            sub_dict = {}
+
+            if "reported_financials" in item:
+                key = "reported_financials"
+                sub_tag = "xbrl_tag"
+            elif "standardized_financials" in item:
+                key = "standardized_financials"
+                sub_tag = "data_tag"
+
+            for sub_item in item[key]:
+                try:
+                    sub_dict[sub_item[sub_tag]["tag"]] = int(
+                        sub_item[sub_tag]["factor"] + str(sub_item["value"])
+                    )
+                except (ValueError, KeyError):
+                    sub_dict[sub_item[sub_tag]["tag"]] = int(sub_item["value"])
+
+            sub_dict["date"] = item["fundamental"]["end_date"]
+            sub_dict["period"] = item["fundamental"]["fiscal_period"]
+            sub_dict["cik"] = item["fundamental"]["company"]["cik"]
+            sub_dict["symbol"] = item["fundamental"]["company"]["ticker"]
+
+            transformed_data.append(IntrinioCashFlowStatementData(**sub_dict))
+
+        return transformed_data
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/forex_pairs.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/forex_pairs.py
new file mode 100644
index 00000000000..f73bc337f96
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/forex_pairs.py
@@ -0,0 +1,73 @@
+"""Intrinio Forex available pairs fetcher."""
+
+
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.forex_pairs import (
+    ForexPairsData,
+    ForexPairsQueryParams,
+)
+from pydantic import Field
+
+from openbb_intrinio.utils.helpers import get_data_many
+
+
+class IntrinioForexPairsQueryParams(ForexPairsQueryParams):
+    """Intrinio Forex available pairs Query.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_forex_pairs_v2
+    """
+
+
+class IntrinioForexPairsData(ForexPairsData):
+    """Intrinio Forex available pairs Data."""
+
+    class Config:
+        fields = {
+            "name": "code",
+        }
+
+    code: str = Field(description="Code of the currency pair.")
+    base_currency: str = Field(
+        description="ISO 4217 currency code of the base currency."
+    )
+    quote_currency: str = Field(
+        description="ISO 4217 currency code of the quote currency."
+    )
+
+
+class IntrinioForexPairsFetcher(
+    Fetcher[
+        IntrinioForexPairsQueryParams,
+        List[IntrinioForexPairsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioForexPairsQueryParams:
+        """Transform the query params."""
+
+        return IntrinioForexPairsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioForexPairsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        url = f"{base_url}/forex/pairs?api_key={api_key}"
+
+        return get_data_many(url, "pairs", **kwargs)
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioForexPairsData]:
+        """Return the transformed data."""
+
+        return [IntrinioForexPairsData(**d) for d in data]
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/global_news.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/global_news.py
new file mode 100644
index 00000000000..913754fc2a6
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/global_news.py
@@ -0,0 +1,117 @@
+"""Intrinio Global News fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.global_news import (
+    GlobalNewsData,
+    GlobalNewsQueryParams,
+)
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, validator
+
+from openbb_intrinio.utils.helpers import get_data_one
+
+
+class IntrinioGlobalNewsQueryParams(GlobalNewsQueryParams):
+    """Intrinio Global News query.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_all_company_news_v2
+    """
+
+    next_page: str = Field(
+        default=None,
+        description="Token to get the next page of data from a previous API call.",
+    )
+    limit: Optional[int] = Field(
+        default=10, description="The number of data entries to return."
+    )
+    all_pages: Optional[bool] = Field(
+        default=False,
+        description="Returns all pages of data from the API call at once.",
+    )
+
+
+class IntrinioGlobalNewsData(GlobalNewsData):
+    """Intrinio Global News Data."""
+
+    class Config:
+        """Pydantic alias config using fields dict."""
+
+        fields = {
+            "date": "publication_date",
+            "text": "summary",
+        }
+
+    id: str = Field(description="Intrinio ID for the news article.")
+    company: Dict[str, Any] = Field(
+        description="Company details related to the news article."
+    )
+
+    @validator("publication_date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S.000Z")
+
+
+class IntrinioGlobalNewsFetcher(
+    Fetcher[
+        IntrinioGlobalNewsQueryParams,
+        List[IntrinioGlobalNewsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioGlobalNewsQueryParams:
+        """Transform the query params."""
+
+        return IntrinioGlobalNewsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioGlobalNewsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        query_str = get_querystring(query.dict(by_alias=True), ["all_pages", "page"])
+        query_str = query_str.replace("limit", "page_size")
+        url = f"{base_url}/companies/news?{query_str}&api_key={api_key}"
+
+        data = get_data_one(url, **kwargs)
+
+        if query.all_pages:
+            all_data = data["news"]
+            next_page = data["next_page"]
+
+            while next_page:
+                query_str = get_querystring(
+                    query.dict(by_alias=True), ["page", "next_page", "all_pages"]
+                )
+                query_str = query_str.replace("limit", "page_size")
+                url = (
+                    f"{base_url}/companies/news?{query_str}&next_page={next_page}"
+                    f"&api_key={api_key}"
+                )
+
+                data = get_data_one(url, **kwargs)
+                all_data.extend(data.get("news", []))
+
+                next_page = data.get("next_page", None)
+
+            return all_data["news"]
+
+        return data.get("news", [])
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioGlobalNewsData]:
+        """Return the transformed data."""
+
+        return [IntrinioGlobalNewsData(**d) for d in data]
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/income_statement.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/income_statement.py
new file mode 100644
index 00000000000..cf9fca94413
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/income_statement.py
@@ -0,0 +1,123 @@
+"""Intrinio Income Statement Fetcher."""
+
+
+from datetime import date
+from typing import Any, Dict, List, Literal, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.income_statement import (
+    IncomeStatementData,
+    IncomeStatementQueryParams,
+)
+from pydantic import Field
+
+from openbb_intrinio.utils.helpers import get_data_one
+
+
+class IntrinioIncomeStatementQueryParams(IncomeStatementQueryParams):
+    """Intrinio Income Statement QueryParams.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_fundamental_reported_financials_v2
+    Source: https://docs.intrinio.com/documentation/web_api/get_fundamental_standardized_financials_v2
+    """
+
+    type: Literal["reported", "standardized"] = Field(
+        default="reported", description="Type of the statement to be fetched."
+    )
+    year: Optional[int] = Field(
+        description="Year of the statement to be fetched.",
+    )
+
+
+class IntrinioIncomeStatementData(IncomeStatementData):
+    """Intrinio Income Statement Data."""
+
+    class Config:
+        fields = {
+            "research_and_development_expenses": "ResearchAndDevelopmentExpense",
+            "selling_general_and_administrative_expenses": "SellingGeneralAndAdministrativeExpense",
+            "operating_income": "OperatingIncomeLoss",
+            "income_before_tax": "IncomeLossFromContinuingOperationsBeforeIncomeTaxesExtraordinaryItemsNoncontrollingInterest",  # noqa: E501
+            "eps_diluted": "EarningsPerShareDiluted",
+            "weighted_average_shares_outstanding": "WeightedAverageNumberOfSharesOutstandingBasic",
+            "weighted_average_shares_outstanding_dil": "WeightedAverageNumberOfDilutedSharesOutstanding",
+        }
+
+
+class IntrinioIncomeStatementFetcher(
+    Fetcher[
+        IntrinioIncomeStatementQueryParams,
+        List[IntrinioIncomeStatementData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioIncomeStatementQueryParams:
+        """Transform the query params."""
+        transform_params = params
+
+        if not params.get("year"):
+            transform_params["year"] = date.today().year - 1
+
+        return IntrinioIncomeStatementQueryParams(**transform_params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioIncomeStatementQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        url_params = f"{query.symbol}-balance_sheet_statement-{query.year}"
+        statement_param = f"{query.type}_financials"
+
+        data = []
+
+        if query.period == "annual":
+            url = f"{base_url}/fundamentals/{url_params}-FY/{statement_param}?api_key={api_key}"
+            data.append(get_data_one(url, **kwargs))
+
+        elif query.period == "quarter":
+            # TODO: Fix quarter range after Intrinio's response
+            for quarter in range(1, 4):
+                url = f"{base_url}/fundamentals/{url_params}-Q{quarter}/{statement_param}?api_key={api_key}"
+                data.append(get_data_one(url, **kwargs))
+
+        return data
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioIncomeStatementData]:
+        """Return the transformed data."""
+
+        transformed_data = []
+
+        for item in data:
+            sub_dict = {}
+
+            if "reported_financials" in item:
+                key = "reported_financials"
+                sub_tag = "xbrl_tag"
+            elif "standardized_financials" in item:
+                key = "standardized_financials"
+                sub_tag = "data_tag"
+
+            for sub_item in item[key]:
+                try:
+                    sub_dict[sub_item[sub_tag]["tag"]] = int(
+                        sub_item[sub_tag]["factor"] + str(sub_item["value"])
+                    )
+                except (ValueError, KeyError):
+                    sub_dict[sub_item[sub_tag]["tag"]] = int(sub_item["value"])
+
+            sub_dict["date"] = item["fundamental"]["end_date"]
+            sub_dict["period"] = item["fundamental"]["fiscal_period"]
+            sub_dict["cik"] = item["fundamental"]["company"]["cik"]
+            sub_dict["symbol"] = item["fundamental"]["company"]["ticker"]
+
+            transformed_data.append(IntrinioIncomeStatementData(**sub_dict))
+
+        return transformed_data
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/options_chains.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/options_chains.py
new file mode 100644
index 00000000000..b0ed1b96dba
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/options_chains.py
@@ -0,0 +1,328 @@
+"""Intrinio Options Chains fetcher."""
+
+import concurrent.futures
+from datetime import (
+    date as dateType,
+    datetime,
+    timedelta,
+)
+from typing import Any, Dict, List, Optional, Union
+
+import pandas as pd
+import requests_cache
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.options_chains import (
+    OptionsChainsData,
+    OptionsChainsQueryParams,
+)
+from openbb_provider.utils.helpers import make_request
+from pydantic import Field, validator
+
+TICKER_EXCEPTIONS = [
+    "SPX",
+    "XSP",
+    "XEO",
+    "NDX",
+    "XND",
+    "VIX",
+    "RUT",
+    "MRUT",
+    "DJX",
+    "XAU",
+    "OEX",
+]
+
+intrinio_session = requests_cache.CachedSession(
+    "OpenBB_Intrinio", expire_after=timedelta(days=5), use_cache_dir=True
+)
+
+
+def get_options_tickers(api_key: str) -> List[str]:
+    """Returns all tickers that have existing options contracts.
+
+    Parameters
+    ----------
+    api_key: str
+        Intrinio API key.
+
+    Returns
+    -------
+    List[str]
+        List of tickers
+    """
+
+    url = f"https://api-v2.intrinio.com/options/tickers?api_key={api_key}"
+
+    r = intrinio_session.get(url, timeout=10)
+
+    return r.json()["tickers"]
+
+
+def get_options_expirations(
+    symbol: str,
+    api_key: str,
+    after: Optional[Union[datetime, str]] = datetime.now().strftime("%Y-%m-%d"),
+    before: Optional[str] = "",
+) -> list:
+    """Returns a list of all current and upcoming option contract expiration dates for a particular symbol.
+
+    Parameters
+    ----------
+    symbol: str
+        The options symbol, corresponding to the underlying security.
+    api_key: str
+        Intrinio API key.
+    after: str
+        Return option contract expiration dates after this date. Format: YYYY-MM-DD
+    before: str
+        Return option contract expiration dates before this date. Format: YYYY-MM-DD
+    """
+
+    url = f"https://api-v2.intrinio.com/options/expirations/{symbol}/eod?before={before}&after={after}&api_key={api_key}"
+
+    r = make_request(url)
+
+    expirations = pd.DatetimeIndex(sorted(list(r.json()["expirations"])))
+    return list(filter(lambda x: x > pd.to_datetime(after), expirations))
+
+
+def generate_url(symbol, expiration, date, api_key):
+    return f"https://api-v2.intrinio.com/options/chain/{symbol}/{expiration}/eod?date={date}&api_key={api_key}"
+
+
+def download_json_files(urls):
+    results = []  # List to store the downloaded JSON data
+
+    def download_single_file(url):
+        response = make_request(url)
+        json_data = response.json()
+        results.append(json_data["chain"])
+
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        executor.map(download_single_file, urls)
+
+    return results
+
+
+def get_historical_chain_with_greeks(
+    symbol: str, date: Optional[Union[str, dateType]] = "", api_key: str = ""
+):
+    symbol = symbol.upper()
+    SYMBOLS = get_options_tickers(api_key)
+    if symbol not in SYMBOLS:
+        raise RuntimeError(f"{symbol}", "is not supported by Intrinio.")
+
+    if not date:
+        date = datetime.now().strftime("%Y-%m-%d")
+
+    # If the symbol is an index, it needs to be preceded with, $.
+    if symbol in TICKER_EXCEPTIONS:
+        symbol = "$" + symbol
+
+    expirations = get_options_expirations(symbol=symbol, api_key=api_key, after=date)
+    urls = []
+
+    for expiration in expirations:
+        urls.append(generate_url(symbol, expiration, date, api_key))
+
+    results = download_json_files(urls)
+
+    if len(results) == 0:
+        date = pd.to_datetime(date) + timedelta(days=-1)
+        for expiration in expirations:
+            urls.append(generate_url(symbol, expiration, date, api_key))
+        results = download_json_files(urls)
+
+    df = pd.DataFrame()
+
+    for i in range(0, len(results)):
+        chains = results[i]
+
+        contract_symbol: List[str] = []
+        expiry: List[str] = []
+        strikes: List[float] = []
+        option_type: List[str] = []
+        close: List[float] = []
+        close_bid: List[float] = []
+        close_ask: List[float] = []
+        volume: List[int] = []
+        open: List[float] = []
+        open_bid: List[float] = []
+        open_ask: List[float] = []
+        open_interest: List[int] = []
+        high: List[float] = []
+        low: List[float] = []
+        mark: List[float] = []
+        ask_high: List[float] = []
+        ask_low: List[float] = []
+        bid_high: List[float] = []
+        bid_low: List[float] = []
+        implied_volatility: List[float] = []
+        delta: List[float] = []
+        gamma: List[float] = []
+        theta: List[float] = []
+        vega: List[float] = []
+        eod_date: List[str] = []
+
+        for item in chains:
+            contract_symbol.append(item["option"]["code"])
+            expiry.append(item["option"]["expiration"])
+            strikes.append(item["option"]["strike"])
+            option_type.append(item["option"]["type"])
+            close.append(item["prices"]["close"])
+            close_bid.append(item["prices"]["close_bid"])
+            close_ask.append(item["prices"]["close_ask"])
+            volume.append(item["prices"]["volume"])
+            open.append(item["prices"]["open"])
+            open_bid.append(item["prices"]["open_bid"])
+            open_ask.append(item["prices"]["open_ask"])
+            open_interest.append(item["prices"]["open_interest"])
+            high.append(item["prices"]["high"])
+            low.append(item["prices"]["low"])
+            mark.append(item["prices"]["mark"])
+            ask_high.append(item["prices"]["ask_high"])
+            ask_low.append(item["prices"]["ask_low"])
+            bid_high.append(item["prices"]["bid_high"])
+            bid_low.append(item["prices"]["bid_low"])
+            implied_volatility.append(item["prices"]["implied_volatility"])
+            delta.append(item["prices"]["delta"])
+            gamma.append(item["prices"]["gamma"])
+            theta.append(item["prices"]["theta"])
+            vega.append(item["prices"]["vega"])
+            eod_date.append(item["prices"]["date"])
+
+        data = pd.DataFrame()
+        data["contract_symbol"] = contract_symbol
+        data["expiration"] = expiry
+        data["strike"] = strikes
+        data["option_type"] = option_type
+        data["close"] = close
+        data["close_bid"] = close_bid
+        data["close_ask"] = close_ask
+        data["volume"] = volume
+        data["open"] = open
+        data["open_bid"] = open_bid
+        data["open_ask"] = open_ask
+        data["open_interest"] = open_interest
+        data["high"] = high
+        data["low"] = low
+        data["mark"] = mark
+        data["bid_high"] = bid_high
+        data["ask_high"] = ask_high
+        data["bid_low"] = bid_low
+        data["ask_low"] = ask_low
+        data["implied_volatility"] = implied_volatility
+        data["delta"] = delta
+        data["gamma"] = gamma
+        data["theta"] = theta
+        data["vega"] = vega
+        data["eod_date"] = eod_date
+
+        data = data.set_index(["expiration", "strike", "option_type"]).sort_index()
+
+        df = pd.concat([df, data])
+
+    df = df.sort_index().reset_index()
+    now = pd.DatetimeIndex(df["eod_date"])
+    temp = pd.DatetimeIndex(df["expiration"])
+    temp_ = (temp - now).days + 1
+    df["dte"] = temp_
+
+    return df
+
+
+class IntrinioOptionsChainsQueryParams(OptionsChainsQueryParams):
+    """Get the complete options chains (Historical) for a ticker from Intrinio.
+
+    source: https://docs.intrinio.com/documentation/web_api/get_options_chain_eod_v2
+    """
+
+    date: Optional[Union[str, dateType]] = Field(
+        description="Date for which the options chains are returned.",
+        default="",
+    )
+
+
+class IntrinioOptionsChainsData(OptionsChainsData):
+    """Intrinio Options Chains Data."""
+
+    class Config:
+        fields = {
+            "bid": "close_bid",
+            "ask": "close_ask",
+        }
+
+    mark: Optional[float] = Field(
+        description="The mid-price between the latest bid-ask spread."
+    )
+    open_bid: Optional[float] = Field(
+        description="The lowest bid price for the option that day."
+    )
+    open_ask: Optional[float] = Field(
+        description="The lowest ask price for the option that day."
+    )
+    bid_low: Optional[float] = Field(
+        description="The lowest bid price for the option that day."
+    )
+    ask_low: Optional[float] = Field(
+        description="The lowest ask price for the option that day."
+    )
+    bid_high: Optional[float] = Field(
+        description="The highest bid price for the option that day."
+    )
+    ask_high: Optional[float] = Field(
+        description="The highest ask price for the option that day."
+    )
+    open: Optional[float] = Field(description="The open price for the option that day.")
+    high: Optional[float] = Field(description="The high price for the option that day.")
+    low: Optional[float] = Field(description="The low price for the option that day.")
+    close: Optional[float] = Field(
+        description="The close price for the option that day."
+    )
+    implied_volatility: Optional[float] = Field(
+        description="The implied volatility for the option at the end of day."
+    )
+    delta: Optional[float] = Field(description="The delta value at the end of day.")
+    gamma: Optional[float] = Field(description="The gamma value at the end of day.")
+    vega: Optional[float] = Field(description="The vega value at the end of day.")
+    theta: Optional[float] = Field(description="The theta value at the end of day.")
+    eod_date: Optional[dateType] = Field(
+        description="Historical date for which the options chains data is from.",
+    )
+    dte: Optional[int] = Field(description="The number of days until expiry.")
+
+    @validator("expiration", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the datetime object from the date string"""
+        return datetime.strptime(v, "%Y-%m-%d")
+
+
+class IntrinioOptionsChainsFetcher(
+    Fetcher[IntrinioOptionsChainsQueryParams, List[IntrinioOptionsChainsData]]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints"""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioOptionsChainsQueryParams:
+        """Transform the query"""
+        return IntrinioOptionsChainsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioOptionsChainsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint"""
+
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+        data = get_historical_chain_with_greeks(
+            symbol=query.symbol, date=query.date, api_key=api_key
+        )
+
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioOptionsChainsData]:
+        """Return the transformed data."""
+        return [IntrinioOptionsChainsData(**d) for d in data]
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_historical.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_historical.py
new file mode 100644
index 00000000000..d178d1f4a02
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_historical.py
@@ -0,0 +1,177 @@
+"""Intrinio Stocks end of day fetcher."""
+
+from datetime import datetime, time
+from typing import Any, Dict, List, Literal, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_historical import (
+    StockHistoricalData,
+    StockHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, NonNegativeInt, validator
+
+from openbb_intrinio.utils.helpers import get_data_one
+from openbb_intrinio.utils.references import INTERVALS, TIMEZONES
+
+
+class IntrinioStockHistoricalQueryParams(StockHistoricalQueryParams):
+    """Intrinio Stock end of day Query.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_security_interval_prices_v2
+    """
+
+    symbol: str = Field(
+        description="A Security identifier (Ticker, FIGI, ISIN, CUSIP, Intrinio ID)."
+    )
+    timezone: Optional[TIMEZONES] = Field(
+        default="UTC", description="Returns trading times in this timezone."
+    )
+    source: Optional[Literal["realtime", "delayed", "nasdaq_basic"]] = Field(
+        default="realtime", description="The source of the data."
+    )
+    start_time: Optional[time] = Field(
+        description="Return intervals starting at the specified time on the `start_date` formatted as 'hh:mm:ss'."
+    )
+    end_time: Optional[time] = Field(
+        description="Return intervals stopping at the specified time on the `end_date` formatted as 'hh:mm:ss'."
+    )
+    interval_size: Optional[INTERVALS] = Field(
+        default="60m", description=QUERY_DESCRIPTIONS.get("frequency", "")
+    )
+    limit: Optional[NonNegativeInt] = Field(
+        default=300,
+        description=f"{QUERY_DESCRIPTIONS.get('limit', '')}. Max value allowed is 300.",
+    )
+    next_page: Optional[str] = Field(
+        description="Token to get the next page of data from a previous API call."
+    )
+    all_pages: Optional[bool] = Field(
+        default=False,
+        description="Returns all pages of data from the API call at once.",
+    )
+
+    @validator("limit", pre=True)
+    def limit_check(cls, v):  # pylint: disable=E0213
+        """Set the limit bound to 300."""
+        return min(v, 300)
+
+
+class IntrinioStockHistoricalData(StockHistoricalData):
+    """Intrinio Stock end of day Data."""
+
+    class Config:
+        fields = {
+            "date": "time",
+        }
+
+    close_time: Optional[datetime] = Field(
+        description="The timestamp that represents the end of the interval span."
+    )
+    interval: Optional[str] = Field(description="The data time frequency.")
+    average: Optional[float] = Field(
+        description="Average trade price of an individual stock during the interval."
+    )
+    change: Optional[float] = Field(
+        description="Change in the price of the symbol from the previous day.",
+        alias="change",
+    )
+
+    @validator("time", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return (
+            datetime.fromisoformat(v.replace("Z", "+00:00"))
+            if v.endswith(("Z", "+00:00"))
+            else datetime.fromisoformat(v)
+        )
+
+    @validator("close_time", pre=True, check_fields=False)
+    def close_time_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return (
+            datetime.fromisoformat(v.replace("Z", "+00:00"))
+            if v.endswith(("Z", "+00:00"))
+            else datetime.fromisoformat(v)
+        )
+
+
+class IntrinioStockHistoricalFetcher(
+    Fetcher[
+        IntrinioStockHistoricalQueryParams,
+        List[IntrinioStockHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioStockHistoricalQueryParams:
+        """Transform the query params."""
+
+        transformed_params = params
+
+        now = datetime.now().date()
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+
+        if params.get("start_time") is None:
+            transformed_params["start_time"] = time(0, 0, 0)
+
+        if params.get("end_time") is None:
+            transformed_params["end_time"] = time(23, 59, 59)
+
+        return IntrinioStockHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioStockHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        query_str = get_querystring(query.dict(by_alias=True), ["symbol", "all_pages"])
+        query_str = query_str.replace("limit", "page_size")
+        url = (
+            f"{base_url}/securities/{query.symbol}/prices/intervals"
+            f"?{query_str}&api_key={api_key}"
+        )
+
+        data = get_data_one(url, **kwargs)
+
+        if query.all_pages:
+            all_data = data["intervals"]
+            next_page = data["next_page"]
+
+            while next_page:
+                query_str = get_querystring(
+                    query.dict(by_alias=True), ["symbol", "next_page", "all_pages"]
+                )
+                query_str = query_str.replace("limit", "page_size")
+                url = (
+                    f"{base_url}/securities/{query.symbol}/prices/intervals"
+                    f"?{query_str}&next_page={next_page}&api_key={api_key}"
+                )
+
+                data = get_data_one(url, **kwargs)
+                all_data.extend(data.get("intervals", []))
+
+                next_page = data.get("next_page", None)
+
+            return all_data
+
+        return data.get("intervals", [])
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioStockHistoricalData]:
+        """Return the transformed data."""
+
+        return [IntrinioStockHistoricalData(**d) for d in data]
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_news.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_news.py
new file mode 100644
index 00000000000..ae6a99466ee
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_news.py
@@ -0,0 +1,99 @@
+"""Intrinio Stock News fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_news import (
+    StockNewsData,
+    StockNewsQueryParams,
+)
+from openbb_provider.utils.helpers import get_querystring
+from pydantic import Field, validator
+
+from openbb_intrinio.utils.helpers import get_data_many
+
+
+class IntrinioStockNewsQueryParams(StockNewsQueryParams):
+    """Intrinio Stock News query.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_company_news_v2
+    """
+
+    class Config:
+        """Pydantic alias config using fields dict."""
+
+        fields = {
+            "symbols": "symbols",
+            "page": "next_page",
+            "limit": "page_size",
+        }
+
+    symbols: str = Field(
+        description="A Company identifier (Ticker, CIK, LEI, Intrinio ID)."
+    )
+    next_page: Optional[str] = Field(
+        description="Token to get the next page of data from a previous API call."
+    )
+    # TODO: Add support for all_pages
+    all_pages: Optional[bool] = Field(
+        default=False,
+        description="Returns all pages of data from the API call at once.",
+    )
+
+
+class IntrinioStockNewsData(StockNewsData):
+    """Intrinio Stock News data."""
+
+    class Config:
+        """Pydantic alias config using fields dict."""
+
+        fields = {
+            "date": "publication_date",
+            "text": "summary",
+        }
+
+    id: str = Field(description="Intrinio ID for the news article.")
+
+    @validator("publication_date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S.000Z")
+
+
+class IntrinioStockNewsFetcher(
+    Fetcher[
+        IntrinioStockNewsQueryParams,
+        List[IntrinioStockNewsData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioStockNewsQueryParams:
+        """Transform the query params."""
+
+        return IntrinioStockNewsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioStockNewsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        """Return the raw data from the Intrinio endpoint."""
+
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        query_str = get_querystring(query.dict(by_alias=True), ["symbols", "all_pages"])
+        url = f"{base_url}/companies/{query.symbols}/news?{query_str}&api_key={api_key}"
+
+        return get_data_many(url, "news", **kwargs)
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[IntrinioStockNewsData]:
+        """Return the transformed data."""
+
+        return [IntrinioStockNewsData(**d) for d in data]
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_quote.py b/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_quote.py
new file mode 100644
index 00000000000..f5509fa8c00
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/models/stock_quote.py
@@ -0,0 +1,128 @@
+"""Intrinio Stock Quote fetcher."""
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_quote import (
+    StockQuoteData,
+    StockQuoteQueryParams,
+)
+from pydantic import Field, validator
+
+from openbb_intrinio.utils.helpers import get_data_one
+from openbb_intrinio.utils.references import SOURCES
+
+
+class IntrinioStockQuoteQueryParams(StockQuoteQueryParams):
+    """Intrinio Stock Quote Query.
+
+    Source: https://docs.intrinio.com/documentation/web_api/get_security_realtime_price_v2
+    """
+
+    symbol: str = Field(
+        description="A Security identifier (Ticker, FIGI, ISIN, CUSIP, Intrinio ID)."
+    )
+    source: SOURCES = Field(default="iex", description="Source of the data.")
+
+
+class IntrinioStockQuoteData(StockQuoteData):
+    """Intrinio Stock Quote Data."""
+
+    class Config:
+        """Pydantic alias config using fields dict."""
+
+        fields = {
+            "day_low": "low_price",
+            "day_high": "high_price",
+            "date": "last_time",
+        }
+
+    last_price: float = Field(description="Price of the last trade.")
+    last_time: datetime = Field(
+        description="Date and Time when the last trade occurred."
+    )
+    last_size: int = Field(description="Size of the last trade.")
+    bid_price: float = Field(description="Price of the top bid order.")
+    bid_size: int = Field(description="Size of the top bid order.")
+    ask_price: float = Field(description="Price of the top ask order.")
+    ask_size: int = Field(description="Size of the top ask order.")
+    open_price: float = Field(description="Open price for the trading day.")
+    close_price: Optional[float] = Field(
+        description="Closing price for the trading day (IEX source only)."
+    )
+    high_price: float = Field(description="High Price for the trading day.")
+    low_price: float = Field(description="Low Price for the trading day.")
+    exchange_volume: Optional[int] = Field(
+        description="Number of shares exchanged during the trading day on the exchange."
+    )
+    market_volume: Optional[int] = Field(
+        description="Number of shares exchanged during the trading day for the whole market."
+    )
+    updated_on: datetime = Field(
+        description="Date and Time when the data was last updated."
+    )
+    source: str = Field(description="Source of the data.")
+    listing_venue: Optional[str] = Field(
+        description="Listing venue where the trade took place (SIP source only)."
+    )
+    sales_conditions: Optional[str] = Field(
+        description="Indicates any sales condition modifiers associated with the trade."
+    )
+    quote_conditions: Optional[str] = Field(
+        description="Indicates any quote condition modifiers associated with the trade."
+    )
+    market_center_code: Optional[str] = Field(
+        description="Market center character code."
+    )
+    is_darkpool: Optional[bool] = Field(
+        description="Whether or not the current trade is from a darkpool."
+    )
+
+    @validator("last_time", "updated_on", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the date as a datetime object."""
+        return (
+            datetime.fromisoformat(v.replace("Z", "+00:00"))
+            if v.endswith(("Z", "+00:00"))
+            else datetime.fromisoformat(v)
+        )
+
+
+class IntrinioStockQuoteFetcher(
+    Fetcher[
+        IntrinioStockQuoteQueryParams,
+        List[IntrinioStockQuoteData],
+    ]
+):
+    """Transform the query, extract and transform the data from the Intrinio endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> IntrinioStockQuoteQueryParams:
+        """Transform the query params."""
+
+        return IntrinioStockQuoteQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: IntrinioStockQuoteQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> Dict:
+        """Return the raw data from the Intrinio endpoint."""
+
+        api_key = credentials.get("intrinio_api_key") if credentials else ""
+
+        base_url = "https://api-v2.intrinio.com"
+        url = f"{base_url}/securities/{query.symbol}/prices/realtime?source={query.source}&api_key={api_key}"
+
+        return get_data_one(url, **kwargs)
+
+    @staticmethod
+    def transform_data(data: Dict) -> IntrinioStockQuoteData:
+        """Return the transformed data."""
+
+        del data["messages"]
+        del data["security"]
+
+        return IntrinioStockQuoteData(**data)
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/utils/__init__.py b/openbb_sdk/providers/intrinio/openbb_intrinio/utils/__init__.py
new file mode 100644
index 00000000000..f46961441f6
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/utils/__init__.py
@@ -0,0 +1 @@
+"""yfinance utils directory."""
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/utils/helpers.py b/openbb_sdk/providers/intrinio/openbb_intrinio/utils/helpers.py
new file mode 100644
index 00000000000..e383194cf4d
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/utils/helpers.py
@@ -0,0 +1,171 @@
+"""Intrinio Helpers Module."""
+
+import json
+from datetime import datetime, timedelta
+from io import StringIO
+from typing import Any, List, Optional, TypeVar, Union
+
+import requests
+import requests_cache
+from openbb_provider import helpers
+from openbb_provider.utils.helpers import make_request
+from pydantic import BaseModel
+from requests.exceptions import SSLError
+
+T = TypeVar("T", bound=BaseModel)
+
+
+# This will cache the symbol directory requests for 5 days.
+intrinio_session = requests_cache.CachedSession(
+    "OpenBB_Intrinio", expire_after=timedelta(days=5), use_cache_dir=True
+)
+
+
+def get_options_tickers(api_key: str = "") -> List[str]:
+    """Returns all tickers that have existing options contracts.
+
+    Parameters
+    ----------
+    api_key: str
+        Intrinio API key.
+
+    Returns
+    -------
+    List[str]
+        List of tickers
+    """
+    url = f"https://api-v2.intrinio.com/options/tickers?api_key={api_key}"
+
+    r = intrinio_session.get(url, timeout=10)
+
+    return r.json()["tickers"]
+
+
+def get_options_expirations(
+    symbol: str,
+    after: Optional[str] = datetime.now().date().strftime("%Y-%m-%d"),
+    before: Optional[str] = "",
+    api_key: str = "",
+) -> list:
+    """Returns a list of all current and upcoming option contract expiration dates for a particular symbol.
+
+    Parameters
+    ----------
+    symbol: str
+        The options symbol, corresponding to the underlying security.
+    after: str
+        Return option contract expiration dates after this date. Format: YYYY-MM-DD
+    before: str
+        Return option contract expiration dates before this date. Format: YYYY-MM-DD
+    api_key: str
+        Intrinio API key.
+    """
+
+    url = f"https://api-v2.intrinio.com/options/expirations/{symbol}/eod?before={before}&after={after}&api_key={api_key}"
+
+    r = make_request(url)
+
+    return sorted(list(r.json()["expirations"]))
+
+
+class BasicResponse:
+    """Basic Response class."""
+
+    def __init__(self, response: StringIO):
+        """Initialize the BasicResponse class."""
+
+        # Find a way to get the status code
+        self.status_code = 200
+        response.seek(0)
+        self.text = response.read()
+
+    def json(self) -> dict:
+        """Return the response as a dictionary."""
+
+        return json.loads(self.text)
+
+
+def request(url: str) -> BasicResponse:
+    """
+    Request function for PyScript. Pass in Method and make sure to await!
+
+    Parameters:
+    -----------
+    url: str
+        URL to make request to
+
+    Return:
+    -------
+    response: BasicRequest
+        BasicRequest object with status_code and text attributes
+    """
+    # pylint: disable=import-outside-toplevel
+    from pyodide.http import open_url  # type: ignore
+
+    response = open_url(url)
+    return BasicResponse(response)
+
+
+def get_data(url: str, **kwargs: Any) -> Union[list, dict]:
+    """Get data from Intrinio endpoint."""
+
+    try:
+        r: Union[requests.Response, BasicResponse] = helpers.make_request(url, **kwargs)
+    except SSLError:
+        r = request(url)
+    if r.status_code == 404:
+        raise RuntimeError("Intrinio endpoint doesn't exist")
+
+    data = r.json()
+    if r.status_code != 200:
+        message = data.get("message", "unknown error")
+        raise RuntimeError(f"Error in Intrinio request -> {message}")
+
+    if "Error Message" in data:
+        raise RuntimeError("Intrinio Error Message -> " + data["Error Message"])
+
+    if len(data) == 0:
+        raise RuntimeError("No results found. Try adjusting the query parameters.")
+
+    return data
+
+
+def get_data_many(
+    url: str, sub_dict: Optional[str] = None, **kwargs: Any
+) -> List[dict]:
+    """Get data from Intrinio endpoint and convert to list of schemas.
+
+    Parameters:
+    -----------
+    url: str
+        The URL to get the data from.
+    sub_dict: Optional[str]
+        The sub-dictionary to use.
+
+    Returns:
+    --------
+    List[dict]
+        Dictionary of data.
+    """
+    data = get_data(url, **kwargs)
+    if sub_dict and isinstance(data, dict):
+        data = data.get(sub_dict, [])
+    if isinstance(data, dict):
+        raise ValueError("Expected list of dicts, got dict")
+    return data
+
+
+def get_data_one(url: str, **kwargs: Any) -> dict:
+    """Get data from Intrinio endpoint and convert to schema."""
+
+    data = get_data(url, **kwargs)
+    if isinstance(data, list):
+        if len(data) == 0:
+            raise ValueError("Expected dict, got empty list")
+
+        try:
+            data = {i: data[i] for i in range(len(data))} if len(data) > 1 else data[0]
+        except TypeError as e:
+            raise ValueError("Expected dict, got list of dicts") from e
+
+    return data
diff --git a/openbb_sdk/providers/intrinio/openbb_intrinio/utils/references.py b/openbb_sdk/providers/intrinio/openbb_intrinio/utils/references.py
new file mode 100644
index 00000000000..a0479f69c2d
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/openbb_intrinio/utils/references.py
@@ -0,0 +1,168 @@
+from typing import Literal
+
+SOURCES = Literal[
+    "iex",
+    "bats",
+    "bats_delayed",
+    "utp_delayed",
+    "cta_a_delayed",
+    "cta_b_delayed",
+    "intrinio_mx",
+    "intrinio_mx_plus",
+    "delayed_sip",
+]
+
+INTERVALS = Literal["1m", "5m", "10m", "15m", "30m", "60m", "1h"]
+
+TIMEZONES = Literal[
+    "Africa/Algiers",
+    "Africa/Cairo",
+    "Africa/Casablanca",
+    "Africa/Harare",
+    "Africa/Johannesburg",
+    "Africa/Monrovia",
+    "Africa/Nairobi",
+    "America/Argentina/Buenos_Aires",
+    "America/Bogota",
+    "America/Caracas",
+    "America/Chicago",
+    "America/Chihuahua",
+    "America/Denver",
+    "America/Godthab",
+    "America/Guatemala",
+    "America/Guyana",
+    "America/Halifax",
+    "America/Indiana/Indianapolis",
+    "America/Juneau",
+    "America/La_Paz",
+    "America/Lima",
+    "America/Lima",
+    "America/Los_Angeles",
+    "America/Mazatlan",
+    "America/Mexico_City",
+    "America/Mexico_City",
+    "America/Monterrey",
+    "America/Montevideo",
+    "America/New_York",
+    "America/Phoenix",
+    "America/Regina",
+    "America/Santiago",
+    "America/Sao_Paulo",
+    "America/St_Johns",
+    "America/Tijuana",
+    "Asia/Almaty",
+    "Asia/Baghdad",
+    "Asia/Baku",
+    "Asia/Bangkok",
+    "Asia/Bangkok",
+    "Asia/Chongqing",
+    "Asia/Colombo",
+    "Asia/Dhaka",
+    "Asia/Dhaka",
+    "Asia/Hong_Kong",
+    "Asia/Irkutsk",
+    "Asia/Jakarta",
+    "Asia/Jerusalem",
+    "Asia/Kabul",
+    "Asia/Kamchatka",
+    "Asia/Karachi",
+    "Asia/Karachi",
+    "Asia/Kathmandu",
+    "Asia/Kolkata",
+    "Asia/Kolkata",
+    "Asia/Kolkata",
+    "Asia/Kolkata",
+    "Asia/Krasnoyarsk",
+    "Asia/Kuala_Lumpur",
+    "Asia/Kuwait",
+    "Asia/Magadan",
+    "Asia/Muscat",
+    "Asia/Muscat",
+    "Asia/Novosibirsk",
+    "Asia/Rangoon",
+    "Asia/Riyadh",
+    "Asia/Seoul",
+    "Asia/Shanghai",
+    "Asia/Singapore",
+    "Asia/Srednekolymsk",
+    "Asia/Taipei",
+    "Asia/Tashkent",
+    "Asia/Tbilisi",
+    "Asia/Tehran",
+    "Asia/Tokyo",
+    "Asia/Tokyo",
+    "Asia/Tokyo",
+    "Asia/Ulaanbaatar",
+    "Asia/Urumqi",
+    "Asia/Vladivostok",
+    "Asia/Yakutsk",
+    "Asia/Yekaterinburg",
+    "Asia/Yerevan",
+    "Atlantic/Azores",
+    "Atlantic/Cape_Verde",
+    "Atlantic/South_Georgia",
+    "Australia/Adelaide",
+    "Australia/Brisbane",
+    "Australia/Darwin",
+    "Australia/Hobart",
+    "Australia/Melbourne",
+    "Australia/Melbourne",
+    "Australia/Perth",
+    "Australia/Sydney",
+    "Etc/UTC",
+    "UTC",
+    "Europe/Amsterdam",
+    "Europe/Athens",
+    "Europe/Belgrade",
+    "Europe/Berlin",
+    "Europe/Berlin",
+    "Europe/Bratislava",
+    "Europe/Brussels",
+    "Europe/Bucharest",
+    "Europe/Budapest",
+    "Europe/Copenhagen",
+    "Europe/Dublin",
+    "Europe/Helsinki",
+    "Europe/Istanbul",
+    "Europe/Kaliningrad",
+    "Europe/Kiev",
+    "Europe/Lisbon",
+    "Europe/Ljubljana",
+    "Europe/London",
+    "Europe/London",
+    "Europe/Madrid",
+    "Europe/Minsk",
+    "Europe/Moscow",
+    "Europe/Moscow",
+    "Europe/Paris",
+    "Europe/Prague",
+    "Europe/Riga",
+    "Europe/Rome",
+    "Europe/Samara",
+    "Europe/Sarajevo",
+    "Europe/Skopje",
+    "Europe/Sofia",
+    "Europe/Stockholm",
+    "Europe/Tallinn",
+    "Europe/Vienna",
+    "Europe/Vilnius",
+    "Europe/Volgograd",
+    "Europe/Warsaw",
+    "Europe/Zagreb",
+    "Pacific/Apia",
+    "Pacific/Auckland",
+    "Pacific/Auckland",
+    "Pacific/Chatham",
+    "Pacific/Fakaofo",
+    "Pacific/Fiji",
+    "Pacific/Guadalcanal",
+    "Pacific/Guam",
+    "Pacific/Honolulu",
+    "Pacific/Majuro",
+    "Pacific/Midway",
+    "Pacific/Midway",
+    "Pacific/Noumea",
+    "Pacific/Pago_Pago",
+    "Pacific/Port_Moresby",
+    "Pacific/Tongatapu",
+]
diff --git a/openbb_sdk/providers/intrinio/poetry.lock b/openbb_sdk/providers/intrinio/poetry.lock
new file mode 100644
index 00000000000..bbdeb006281
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/poetry.lock
@@ -0,0 +1,1144 @@
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+
+[[package]]
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+optional = false
+python-versions = ">=3.8"
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+    {file = "anyio-4.0.0.tar.gz", hash = "sha256:f7ed51751b2c2add651e5747c891b47e26d2a21be5d32d9311dfe9692f3e5d7a"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.22)"]
+
+[[package]]
+name = "attrs"
+version = "23.1.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.7"
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+]
+
+[package.extras]
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+dev = ["attrs[docs,tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+
+[[package]]
+name = "backoff"
+version = "2.2.1"
+description = "Function decoration for backoff and retry"
+optional = false
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+]
+
+[[package]]
+name = "zipp"
+version = "3.16.2"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
+    {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.8"
+content-hash = "089b57f47762394a09171ba599366e5a5f0aefc8800032cb1ca4fdaed02fd1f1"
diff --git a/openbb_sdk/providers/intrinio/pyproject.toml b/openbb_sdk/providers/intrinio/pyproject.toml
new file mode 100644
index 00000000000..e41db6ee99e
--- /dev/null
+++ b/openbb_sdk/providers/intrinio/pyproject.toml
@@ -0,0 +1,19 @@
+[tool.poetry]
+name = "openbb-intrinio"
+version = "0.1.0"
+description = "Intrinio extension for OpenBB"
+authors = ["OpenBB Team <hello@openbb.co>"]
+readme = "README.md"
+packages = [{ include = "openbb_intrinio" }]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+requests-cache = "^1.1.0"
+openbb-core = { path = "../../sdk/core" }
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.plugins."openbb_provider_extension"]
+intrinio = "openbb_intrinio:intrinio_provider"
diff --git a/openbb_sdk/providers/intrinio/tests/.gitkeep b/openbb_sdk/providers/intrinio/tests/.gitkeep
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/__init__.py b/openbb_sdk/providers/polygon/openbb_polygon/__init__.py
index 042c59d2358..731b554ada9 100644
--- a/openbb_sdk/providers/polygon/openbb_polygon/__init__.py
+++ b/openbb_sdk/providers/polygon/openbb_polygon/__init__.py
@@ -3,12 +3,14 @@ from openbb_provider.abstract.provider import Provider
 
 from openbb_polygon.models.balance_sheet import PolygonBalanceSheetFetcher
 from openbb_polygon.models.cash_flow import PolygonCashFlowStatementFetcher
-from openbb_polygon.models.crypto_eod import PolygonCryptoEODFetcher
-from openbb_polygon.models.forex_eod import PolygonForexEODFetcher
+from openbb_polygon.models.crypto_historical import PolygonCryptoHistoricalFetcher
+from openbb_polygon.models.forex_historical import PolygonForexHistoricalFetcher
 from openbb_polygon.models.forex_pairs import PolygonForexPairsFetcher
 from openbb_polygon.models.income_statement import PolygonIncomeStatementFetcher
-from openbb_polygon.models.major_indices_eod import PolygonMajorIndicesEODFetcher
-from openbb_polygon.models.stock_eod import PolygonStockEODFetcher
+from openbb_polygon.models.major_indices_historical import (
+    PolygonMajorIndicesHistoricalFetcher,
+)
+from openbb_polygon.models.stock_historical import PolygonStockHistoricalFetcher
 from openbb_polygon.models.stock_news import PolygonStockNewsFetcher
 
 polygon_provider = Provider(
@@ -19,14 +21,14 @@ polygon_provider = Provider(
      company financials, stock market holidays, corporate actions, and more.""",
     required_credentials=["api_key"],
     fetcher_dict={
-        "StockEOD": PolygonStockEODFetcher,
+        "StockHistorical": PolygonStockHistoricalFetcher,
         "StockNews": PolygonStockNewsFetcher,
         "BalanceSheet": PolygonBalanceSheetFetcher,
         "IncomeStatement": PolygonIncomeStatementFetcher,
         "CashFlowStatement": PolygonCashFlowStatementFetcher,
-        "CryptoEOD": PolygonCryptoEODFetcher,
-        "MajorIndicesEOD": PolygonMajorIndicesEODFetcher,
-        "ForexEOD": PolygonForexEODFetcher,
+        "CryptoHistorical": PolygonCryptoHistoricalFetcher,
+        "MajorIndicesHistorical": PolygonMajorIndicesHistoricalFetcher,
+        "ForexHistorical": PolygonForexHistoricalFetcher,
         "ForexPairs": PolygonForexPairsFetcher,
     },
 )
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/balance_sheet.py b/openbb_sdk/providers/polygon/openbb_polygon/models/balance_sheet.py
index dd66e0a46e2..2a9b85a7df2 100644
--- a/openbb_sdk/providers/polygon/openbb_polygon/models/balance_sheet.py
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/balance_sheet.py
@@ -21,9 +21,20 @@ class PolygonBalanceSheetData(BalanceSheetData):
 
     class Config:
         fields = {
-            "date": "start_date",
-            "equity": "total_equity",
-            "total_liabilities_and_stockholders_equity": "liabilities_and_equity",
+            "total_current_assets": "current_assets",
+            "marketable_securities": "fixed_assets",
+            "property_plant_equipment_net": "public_utilities_property_plant_and_equipment_net",
+            "other_non_current_assets": "other_noncurrent_assets_of_regulated_entity",
+            "total_non_current_assets": "noncurrent_assets",
+            "total_assets": "assets",
+            "total_current_liabilities": "current_liabilities",
+            "other_non_current_liabilities": "other _noncurrent_liabilities_of_regulated_entity",
+            "total_non_current_liabilities": "noncurrent_liabilities",
+            "total_liabilities": "liabilities",
+            "preferred_stock": "temporary_equity",
+            "total_shareholder_equity": "temporary_equity_attributable_to_parent",
+            "total_equity": "equity",
+            "total_liabilities_and_shareholders_equity": "liabilities_and_equity",
             "minority_interest": "equity_attributable_to_noncontrolling_interest",
         }
 
@@ -66,25 +77,17 @@ class PolygonBalanceSheetFetcher(
     def transform_data(
         data: dict,
     ) -> List[PolygonBalanceSheetData]:
-        FIELDS = [
-            "assets",
-            "current_assets",
-            "current_liabilities",
-            "equity",
-            "equity_attributable_to_noncontrolling_interest",
-            "equity_attributable_to_parent",
-            "liabilities",
-            "liabilities_and_equity",
-            "noncurrent_assets",
-            "noncurrent_liabilities",
-        ]
+        transformed_data = []
 
-        to_return = []
         for item in data:
-            new = {"start_date": item["start_date"], "cik": item["cik"]}
-            if bs := item["financials"]["balance_sheet"]:
-                for field in FIELDS:
-                    new[field] = bs[field].get("value", 0)
+            sub_data = {
+                key: value["value"]
+                for key, value in item["financials"]["balance_sheet"].items()
+            }
+            sub_data["date"] = item["start_date"]
+            sub_data["cik"] = item["cik"]
+            sub_data["symbol"] = item["tickers"]
+            sub_data["period"] = item["fiscal_period"]
+            transformed_data.append(PolygonBalanceSheetData(**sub_data))
 
-            to_return.append(PolygonBalanceSheetData(**new))
-        return to_return
+        return transformed_data
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/cash_flow.py b/openbb_sdk/providers/polygon/openbb_polygon/models/cash_flow.py
index d467ab9eae4..7b4ced4fbda 100644
--- a/openbb_sdk/providers/polygon/openbb_polygon/models/cash_flow.py
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/cash_flow.py
@@ -1,28 +1,26 @@
 from typing import Any, Dict, List, Optional
 
 from openbb_provider.abstract.fetcher import Fetcher
-from openbb_provider.standard_models.cash_flows import CashFlowStatementData
+from openbb_provider.standard_models.cash_flow import CashFlowStatementData
 from openbb_provider.utils.helpers import get_querystring
 from pydantic import validator
 
 from openbb_polygon.utils.helpers import get_data
 from openbb_polygon.utils.types import PolygonFundamentalQueryParams
 
-# noqa: E501
-
 
 class PolygonCashFlowStatementQueryParams(PolygonFundamentalQueryParams):
-    __doc__ = PolygonFundamentalQueryParams.__doc__
+    """Polygon Fundamental QueryParams.
+
+    Source: https://polygon.io/docs/stocks#!/get_vx_reference_financials
+    """
 
 
 class PolygonCashFlowStatementData(CashFlowStatementData):
-    """Cash Flow Statement Data."""
-
-    class Config:
-        fields = {"date": "start_date"}
+    """Return Balance Sheet Data."""
 
     @validator("symbol", pre=True, check_fields=False)
-    def symbol_from_tickers(cls, v):
+    def symbol_from_tickers(cls, v):  # pylint: disable=no-self-argument
         if isinstance(v, list):
             return ",".join(v)
         return v
@@ -52,7 +50,7 @@ class PolygonCashFlowStatementFetcher(
         data = get_data(request_url, **kwargs)["results"]
 
         if len(data) == 0:
-            raise RuntimeError("No Cash Flow Statement found")
+            raise RuntimeError("No balance sheet found")
 
         return data
 
@@ -60,23 +58,17 @@ class PolygonCashFlowStatementFetcher(
     def transform_data(
         data: dict,
     ) -> List[PolygonCashFlowStatementData]:
-        FIELDS = [
-            "net_cash_flow_from_financing_activities",
-            "net_cash_flow_from_investing_activities",
-            "net_cash_flow_from_operating_activities",
-            "net_cash_flow_continuing",
-            "net_cash_flow_from_financing_activities_continuing",
-            "net_cash_flow_from_investing_activities_continuing",
-            "net_cash_flow_from_operating_activities_continuing",
-            "net_cash_flow",
-        ]
+        transformed_data = []
 
-        to_return = []
         for item in data:
-            new = {"start_date": item["start_date"], "cik": item["cik"]}
-            if cf := item["financials"]["cash_flow_statement"]:
-                for field in FIELDS:
-                    new[field] = cf[field].get("value", 0)
+            sub_data = {
+                key: value["value"]
+                for key, value in item["financials"]["cash_flow_statement"].items()
+            }
+            sub_data["date"] = item["start_date"]
+            sub_data["cik"] = item["cik"]
+            sub_data["symbol"] = item["tickers"]
+            sub_data["period"] = item["fiscal_period"]
+            transformed_data.append(PolygonCashFlowStatementData(**sub_data))
 
-            to_return.append(PolygonCashFlowStatementData(**new))
-        return to_return
+        return transformed_data
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/crypto_historical.py b/openbb_sdk/providers/polygon/openbb_polygon/models/crypto_historical.py
new file mode 100644
index 00000000000..5b2720df672
--- /dev/null
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/crypto_historical.py
@@ -0,0 +1,112 @@
+"""Polygon crypto end of day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.crypto_historical import (
+    CryptoHistoricalData,
+    CryptoHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, PositiveInt, validator
+
+from openbb_polygon.utils.helpers import get_data
+
+
+class PolygonCryptoHistoricalQueryParams(CryptoHistoricalQueryParams):
+    """Polygon crypto end of day Query.
+
+    Source: https://polygon.io/docs/crypto/get_v2_aggs_ticker__cryptoticker__range__multiplier___timespan___from___to
+    """
+
+    timespan: Literal[
+        "minute", "hour", "day", "week", "month", "quarter", "year"
+    ] = Field(default="day", description="Timespan of the data.")
+    sort: Literal["asc", "desc"] = Field(
+        default="desc", description="Sort order of the data."
+    )
+    limit: PositiveInt = Field(
+        default=49999, description=QUERY_DESCRIPTIONS.get("limit", "")
+    )
+    adjusted: bool = Field(default=True, description="Whether the data is adjusted.")
+    multiplier: PositiveInt = Field(
+        default=1, description="Multiplier of the timespan."
+    )
+
+
+class PolygonCryptoHistoricalData(CryptoHistoricalData):
+    """Polygon crypto end of day Data."""
+
+    class Config:
+        fields = {
+            "date": "t",
+            "open": "o",
+            "high": "h",
+            "low": "l",
+            "close": "c",
+            "volume": "v",
+            "vwap": "vw",
+        }
+
+    n: PositiveInt = Field(
+        description="Number of transactions for the symbol in the time period."
+    )
+
+    @validator("t", pre=True, check_fields=False)
+    def time_validate(cls, v):  # pylint: disable=E0213
+        return datetime.fromtimestamp(v / 1000)
+
+
+class PolygonCryptoHistoricalFetcher(
+    Fetcher[
+        PolygonCryptoHistoricalQueryParams,
+        List[PolygonCryptoHistoricalData],
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> PolygonCryptoHistoricalQueryParams:
+        now = datetime.now().date()
+        transformed_params = params
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+
+        if params.get("symbol"):
+            transformed_params["symbol"] = params["symbol"].replace("-", "")
+
+        return PolygonCryptoHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: PolygonCryptoHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        api_key = credentials.get("polygon_api_key") if credentials else ""
+
+        request_url = (
+            f"https://api.polygon.io/v2/aggs/ticker/"
+            f"X:{query.symbol}/range/{query.multiplier}/{query.timespan}/"
+            f"{query.start_date}/{query.end_date}?adjusted={query.adjusted}"
+            f"&sort={query.sort}&limit={query.limit}&apiKey={api_key}"
+        )
+
+        data = get_data(request_url, **kwargs)
+        if isinstance(data, list):
+            raise ValueError("Expected a dict, got a list")
+
+        if "results" not in data or len(data["results"]) == 0:
+            raise RuntimeError("No results found. Please change your query parameters.")
+
+        return data
+
+    @staticmethod
+    def transform_data(data: dict) -> List[PolygonCryptoHistoricalData]:
+        return [
+            PolygonCryptoHistoricalData.parse_obj(d) for d in data.get("results", [])
+        ]
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/forex_historical.py b/openbb_sdk/providers/polygon/openbb_polygon/models/forex_historical.py
new file mode 100644
index 00000000000..6965f075f11
--- /dev/null
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/forex_historical.py
@@ -0,0 +1,109 @@
+"""Polygon forex end of day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.forex_historical import (
+    ForexHistoricalData,
+    ForexHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, PositiveInt, validator
+
+from openbb_polygon.utils.helpers import get_data
+
+
+class PolygonForexHistoricalQueryParams(ForexHistoricalQueryParams):
+    """Polygon forex end of day Query.
+
+    Source: https://polygon.io/docs/forex/get_v2_aggs_ticker__forexticker__range__multiplier___timespan___from___to
+    """
+
+    timespan: Literal[
+        "minute", "hour", "day", "week", "month", "quarter", "year"
+    ] = Field(default="day", description="Timespan of the data.")
+    sort: Literal["asc", "desc"] = Field(
+        default="desc", description="Sort order of the data."
+    )
+    limit: PositiveInt = Field(
+        default=49999, description=QUERY_DESCRIPTIONS.get("limit", "")
+    )
+    adjusted: bool = Field(default=True, description="Whether the data is adjusted.")
+    multiplier: PositiveInt = Field(
+        default=1, description="Multiplier of the timespan."
+    )
+
+
+class PolygonForexHistoricalData(ForexHistoricalData):
+    """Polygon forex end of day Data."""
+
+    class Config:
+        fields = {
+            "date": "t",
+            "open": "o",
+            "high": "h",
+            "low": "l",
+            "close": "c",
+            "volume": "v",
+            "vwap": "vw",
+        }
+
+    n: PositiveInt = Field(
+        description="Number of transactions for the symbol in the time period."
+    )
+
+    @validator("t", pre=True, check_fields=False)
+    def time_validate(cls, v):  # pylint: disable=E0213
+        return datetime.fromtimestamp(v / 1000)
+
+
+class PolygonForexHistoricalFetcher(
+    Fetcher[
+        PolygonForexHistoricalQueryParams,
+        List[PolygonForexHistoricalData],
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> PolygonForexHistoricalQueryParams:
+        now = datetime.now().date()
+        transformed_params = params
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+
+        return PolygonForexHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: PolygonForexHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        api_key = credentials.get("polygon_api_key") if credentials else ""
+
+        request_url = (
+            f"https://api.polygon.io/v2/aggs/ticker/"
+            f"C:{query.symbol}/range/{query.multiplier}/{query.timespan}/"
+            f"{query.start_date}/{query.end_date}?adjusted={query.adjusted}"
+            f"&sort={query.sort}&limit={query.limit}&apiKey={api_key}"
+        )
+
+        data = get_data(request_url, **kwargs)
+        if isinstance(data, list):
+            raise ValueError("Expected a dict, got a list")
+
+        if "results" not in data or len(data["results"]) == 0:
+            raise RuntimeError("No results found. Please change your query parameters.")
+
+        return data
+
+    @staticmethod
+    def transform_data(data: dict) -> List[PolygonForexHistoricalData]:
+        return [
+            PolygonForexHistoricalData.parse_obj(d) for d in data.get("results", [])
+        ]
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/income_statement.py b/openbb_sdk/providers/polygon/openbb_polygon/models/income_statement.py
index 043b2023e8b..137c562e4e4 100644
--- a/openbb_sdk/providers/polygon/openbb_polygon/models/income_statement.py
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/income_statement.py
@@ -1,10 +1,9 @@
-from datetime import date as dateType
 from typing import Any, Dict, List, Optional
 
 from openbb_provider.abstract.fetcher import Fetcher
 from openbb_provider.standard_models.income_statement import IncomeStatementData
 from openbb_provider.utils.helpers import get_querystring
-from pydantic import validator
+from pydantic import Field, validator
 
 from openbb_polygon.utils.helpers import get_data
 from openbb_polygon.utils.types import PolygonFundamentalQueryParams
@@ -17,35 +16,51 @@ class PolygonIncomeStatementQueryParams(PolygonFundamentalQueryParams):
 class PolygonIncomeStatementData(IncomeStatementData):
     class Config:
         fields = {
-            "date": "start_date",
-            "accepted_date": "acceptance_datetime",
-            "period": "fiscal_period",
-            "revenue": "revenues",
-            "operating_income": "operating_income_loss",
-            "income_before_tax": "income_loss_from_continuing_operations_before_tax",
-            "income_tax_expense": "income_tax_expense_benefit",
-            "net_income": "net_income_loss",
-            "eps": "basic_earnings_per_share",
-            "eps_diluted": "diluted_earnings_per_share",
-            "interest_expense": "interest_expense_operating",
-            "symbol": "tickers",
+            "revenue": "Revenues",
+            "cost_of_revenue": "Cost Of Revenue",
+            "gross_profit": "Gross Profit",
+            "cost_and_expenses": "Costs And Expenses",
+            "operating_expenses": "Operating Expenses",
+            "operating_income": "Operating Income/Loss",
+            "interest_expense": "Interest Expense, Operating",
+            "income_tax_expense": "Income Tax Expense/Benefit",
+            "net_income": "Net Income/Loss",
+            "eps": "Basic Earnings Per Share",
+            "eps_diluted": "Diluted Earnings Per Share",
         }
 
-    # tickers: Optional[List[str]]
-    cik: Optional[str]
-    filing_date: Optional[dateType]
-    cost_of_revenue: Optional[int]
-    gross_profit: Optional[int]
-    operating_expenses: Optional[int]
-    income_loss_from_continuing_operations_after_tax: Optional[float]
-    benefits_costs_expenses: Optional[float]
-    net_income_loss_attributable_to_noncontrolling_interest: Optional[int]
-    net_income_loss_attributable_to_parent: Optional[float]
-    net_income_loss_available_to_common_stockholders_basic: Optional[float]
+    income_loss_from_continuing_operations_before_tax: Optional[float] = Field(
+        description="Income/Loss From Continuing Operations After Tax"
+    )
+    income_loss_from_continuing_operations_after_tax: Optional[float] = Field(
+        description="Income/Loss From Continuing Operations After Tax"
+    )
+    benefits_costs_expenses: Optional[float] = Field(
+        description="Benefits, Costs And Expenses"
+    )
+    net_income_loss_attributable_to_noncontrolling_interest: Optional[float] = Field(
+        description="Net Income/Loss Attributable To Noncontrolling Interest"
+    )
+    net_income_loss_attributable_to_parent: Optional[float] = Field(
+        description="Net Income/Loss Attributable To Parent"
+    )
+    income_tax_expense_benefit_deferred: Optional[float] = Field(
+        description="Income Tax Expense/Benefit Deferred"
+    )
     participating_securities_distributed_and_undistributed_earnings_loss_basic: Optional[
         float
-    ]
-    preferred_stock_dividends_and_other_adjustments: Optional[float]
+    ] = Field(
+        description="Participating Securities Distributed And Undistributed Earnings Loss Basic"
+    )
+    net_income_loss_available_to_common_stockholders_basic: Optional[float] = Field(
+        description="Net Income/Loss Available To Common Stockholders Basic"
+    )
+    nonoperating_income_loss: Optional[float] = Field(
+        description="Nonoperating Income Loss"
+    )
+    preferred_stock_dividends_and_other_adjustments: Optional[float] = Field(
+        description="Preferred Stock Dividends And Other Adjustments"
+    )
 
     @validator("symbol", pre=True, check_fields=False)
     def symbol_from_tickers(cls, v):  # pylint: disable=E0213
@@ -86,39 +101,17 @@ class PolygonIncomeStatementFetcher(
     def transform_data(
         data: dict,
     ) -> List[PolygonIncomeStatementData]:
-        FIELDS = [
-            "revenues",
-            "cost_of_revenue",
-            "gross_profit",
-            "operating_expenses" "income_loss_from_continuing_operations_before_tax",
-            "income_tax_expense_benefit",
-            "net_income_loss",
-            "basic_earnings_per_share",
-            "diluted_earnings_per_share",
-            "net_income_loss_attributable_to_noncontrolling_interest",
-            "net_income_loss_attributable_to_parent",
-            "net_income_loss_available_to_common_stockholders_basic",
-            "operating_income_loss",
-            "participating_securities_distributed_and_undistributed_earnings_loss_basic",
-            "preferred_stock_dividends_and_other_adjustments",
-            "income_loss_from_continuing_operations_after_tax",
-            "benefits_costs_expenses",
-            "interest_expense_operating",
-        ]
+        transformed_data = []
 
-        to_return = []
         for item in data:
-            new = {"acceptance_datetime": item.get("acceptance_datetime")}
-            new["start_date"] = item["start_date"]
-            new["filing_date"] = item.get("filing_date")
-            new["fiscal_period"] = item["fiscal_period"]
-            new["tickers"] = item["tickers"]
-            new["cik"] = item["cik"]
-            incs = item["financials"].get("income_statement", {})
+            sub_data = {
+                key: value["value"]
+                for key, value in item["financials"]["income_statement"].items()
+            }
+            sub_data["date"] = item["start_date"]
+            sub_data["cik"] = item["cik"]
+            sub_data["symbol"] = item["tickers"]
+            sub_data["period"] = item["fiscal_period"]
+            transformed_data.append(PolygonIncomeStatementData(**sub_data))
 
-            if incs:
-                for field in FIELDS:
-                    new[field] = incs.get(field, {}).get("value", 0)
-
-            to_return.append(PolygonIncomeStatementData(**new))
-        return to_return
+        return transformed_data
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/major_indices_historical.py b/openbb_sdk/providers/polygon/openbb_polygon/models/major_indices_historical.py
new file mode 100644
index 00000000000..cae8fe1fe35
--- /dev/null
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/major_indices_historical.py
@@ -0,0 +1,107 @@
+"""Polygon major indices end of day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Literal, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.major_indices_historical import (
+    MajorIndicesHistoricalData,
+    MajorIndicesHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, PositiveInt, validator
+
+from openbb_polygon.utils.helpers import get_data
+
+
+class PolygonMajorIndicesHistoricalQueryParams(MajorIndicesHistoricalQueryParams):
+    """Polygon major indices end of day Query.
+
+    Source: https://polygon.io/docs/indices/getting-started
+    """
+
+    timespan: Literal[
+        "minute", "hour", "day", "week", "month", "quarter", "year"
+    ] = Field(default="day", description="Timespan of the data.")
+    sort: Literal["asc", "desc"] = Field(
+        default="desc", description="Sort order of the data."
+    )
+    limit: PositiveInt = Field(
+        default=49999, description=QUERY_DESCRIPTIONS.get("limit", "")
+    )
+    adjusted: bool = Field(default=True, description="Whether the data is adjusted.")
+    multiplier: PositiveInt = Field(
+        default=1, description="Multiplier of the timespan."
+    )
+
+
+class PolygonMajorIndicesHistoricalData(MajorIndicesHistoricalData):
+    """Polygon major indices end of day Data."""
+
+    class Config:
+        fields = {
+            "date": "t",
+            "open": "o",
+            "high": "h",
+            "low": "l",
+            "close": "c",
+        }
+
+    @validator("t", pre=True, check_fields=False)
+    def time_validate(cls, v):  # pylint: disable=E0213
+        return datetime.fromtimestamp(v / 1000)
+
+
+class PolygonMajorIndicesHistoricalFetcher(
+    Fetcher[
+        PolygonMajorIndicesHistoricalQueryParams,
+        List[PolygonMajorIndicesHistoricalData],
+    ]
+):
+    @staticmethod
+    def transform_query(
+        params: Dict[str, Any]
+    ) -> PolygonMajorIndicesHistoricalQueryParams:
+        now = datetime.now().date()
+        transformed_params = params
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+        return PolygonMajorIndicesHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: PolygonMajorIndicesHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        api_key = credentials.get("polygon_api_key") if credentials else ""
+
+        request_url = (
+            f"https://api.polygon.io/v2/aggs/ticker/"
+            f"I:{query.symbol}/range/{query.multiplier}/{query.timespan}/"
+            f"{query.start_date}/{query.end_date}?adjusted={query.adjusted}"
+            f"&sort={query.sort}&limit={query.limit}&apiKey={api_key}"
+        )
+
+        data = get_data(request_url, **kwargs)
+        if isinstance(data, list):
+            raise ValueError("Expected a dict, got a list")
+
+        if "results" not in data or len(data["results"]) == 0:
+            raise RuntimeError("No results found. Please change your query parameters.")
+
+        return data
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[PolygonMajorIndicesHistoricalData]:
+        return [
+            PolygonMajorIndicesHistoricalData.parse_obj(d)
+            for d in data.get("results", [])
+        ]
diff --git a/openbb_sdk/providers/polygon/openbb_polygon/models/stock_historical.py b/openbb_sdk/providers/polygon/openbb_polygon/models/stock_historical.py
new file mode 100644
index 00000000000..83467765fb6
--- /dev/null
+++ b/openbb_sdk/providers/polygon/openbb_polygon/models/stock_historical.py
@@ -0,0 +1,120 @@
+"""Polygon stocks end of day fetcher."""
+
+
+from concurrent.futures import ThreadPoolExecutor
+from datetime import datetime
+from itertools import repeat
+from typing import Any, Dict, List, Literal, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_historical import (
+    StockHistoricalData,
+    StockHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, PositiveInt, validator
+
+from openbb_polygon.utils.helpers import get_data
+
+
+class PolygonStockHistoricalQueryParams(StockHistoricalQueryParams):
+    """Polygon stocks end of day Query.
+
+    Source: https://polygon.io/docs/stocks/getting-started
+    """
+
+    timespan: Literal[
+        "minute", "hour", "day", "week", "month", "quarter", "year"
+    ] = Field(default="day", description="Timespan of the data.")
+    sort: Literal["asc", "desc"] = Field(
+        default="desc", description="Sort order of the data."
+    )
+    limit: PositiveInt = Field(
+        default=49999, description=QUERY_DESCRIPTIONS.get("limit", "")
+    )
+    adjusted: bool = Field(default=True, description="Whether the data is adjusted.")
+    multiplier: PositiveInt = Field(
+        default=1, description="Multiplier of the timespan."
+    )
+
+
+class PolygonStockHistoricalData(StockHistoricalData):
+    """Polygon stocks end of day Data."""
+
+    class Config:
+        fields = {
+            "date": "t",
+            "open": "o",
+            "high": "h",
+            "low": "l",
+            "close": "c",
+            "volume": "v",
+        }
+
+    vwap: Optional[float] = Field(description="The volume weighted average price.")
+    transactions: Optional[PositiveInt] = Field(
+        description="Number of transactions for the symbol in the time period.",
+        alias="n",
+    )
+
+    @validator("t", pre=True, check_fields=False)
+    def time_validate(cls, v):  # pylint: disable=E0213
+        return datetime.fromtimestamp(v / 1000)
+
+
+class PolygonStockHistoricalFetcher(
+    Fetcher[
+        PolygonStockHistoricalQueryParams,
+        List[PolygonStockHistoricalData],
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> PolygonStockHistoricalQueryParams:
+        now = datetime.now().date()
+        transformed_params = params
+        if params.get("start_date") is None:
+            transformed_params["start_date"] = now - relativedelta(years=1)
+
+        if params.get("end_date") is None:
+            transformed_params["end_date"] = now
+        return PolygonStockHistoricalQueryParams(**transformed_params)
+
+    @staticmethod
+    def extract_data(
+        query: PolygonStockHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[dict]:
+        api_key = credentials.get("polygon_api_key") if credentials else ""
+
+        data: list = []
+
+        def multiple_symbols(
+            symbol: str, data: List[PolygonStockHistoricalData]
+        ) -> None:
+            request_url = (
+                f"https://api.polygon.io/v2/aggs/ticker/"
+                f"{symbol.upper()}/range/{query.multiplier}/{query.timespan}/"
+                f"{query.start_date}/{query.end_date}?adjusted={query.adjusted}"
+                f"&sort={query.sort}&limit={query.limit}&apiKey={api_key}"
+            )
+            results = get_data(request_url, **kwargs).get("results", [])
+
+            if "," in query.symbol:
+                results = [dict(symbol=symbol, **d) for d in results]
+
+            return data.extend(
+                [PolygonStockHistoricalData.parse_obj(d) for d in results]
+            )
+
+        with ThreadPoolExecutor() as executor:
+            executor.map(multiple_symbols, query.symbol.split(","), repeat(data))
+
+        data.sort(key=lambda x: x.date)
+
+        return data
+
+    @staticmethod
+    def transform_data(data: List[dict]) -> List[PolygonStockHistoricalData]:
+        return [PolygonStockHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/quandl/README.md b/openbb_sdk/providers/quandl/README.md
new file mode 100644
index 00000000000..3847a42c4df
--- /dev/null
+++ b/openbb_sdk/providers/quandl/README.md
@@ -0,0 +1,11 @@
+# OpenBB Quandl Provider
+
+This extension integrates the Quandl data provider into the OpenBB SDK.
+
+## Installation
+
+To install the extension, run the following command in this folder:
+
+```bash
+pip install .
+```
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/__init__.py b/openbb_sdk/providers/quandl/openbb_quandl/__init__.py
new file mode 100644
index 00000000000..0b4101e7ad7
--- /dev/null
+++ b/openbb_sdk/providers/quandl/openbb_quandl/__init__.py
@@ -0,0 +1,23 @@
+"""quandl provider module."""
+from openbb_provider.abstract.provider import Provider
+
+from openbb_quandl.models.cot import QuandlCotFetcher
+from openbb_quandl.models.cot_search import QuandlCotSearchFetcher
+from openbb_quandl.models.sp500_multiples import QuandlSP500MultiplesFetcher
+
+quandl_provider = Provider(
+    name="quandl",
+    website="data.nasdaq.com/publishers/qdl",
+    description="""Quandl is a premier publisher of alternative data for institutional investors.
+    A dedicated team of data scientists, quants and engineers combine uncompromising curation,
+    high quality standards and experienced data science application to provide some of the most powerful data available
+    today. Quandl also publishes free data, scraped from the web and delivered via Nasdaq Data Link's
+    industry-leading data delivery platform.
+    """,
+    required_credentials=["api_key"],
+    fetcher_dict={
+        "SP500Multiples": QuandlSP500MultiplesFetcher,
+        "COT": QuandlCotFetcher,
+        "COTSearch": QuandlCotSearchFetcher,
+    },
+)
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/models/__init__.py b/openbb_sdk/providers/quandl/openbb_quandl/models/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/models/cot.py b/openbb_sdk/providers/quandl/openbb_quandl/models/cot.py
new file mode 100644
index 00000000000..280e74bb62b
--- /dev/null
+++ b/openbb_sdk/providers/quandl/openbb_quandl/models/cot.py
@@ -0,0 +1,192 @@
+"""CFTC Commitment of Traders Reports fetcher."""
+
+from datetime import (
+    date as dateType,
+    datetime,
+)
+from typing import Any, Dict, List, Literal, Optional
+
+import pandas as pd
+import quandl
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.utils.helpers import to_snake_case
+from pydantic import Field, validator
+
+from openbb_quandl.utils.series_ids import CFTC
+
+
+class QuandlCotQueryParams(QueryParams):
+    """Get CFTC Commitment of Traders Report.
+
+    Source: https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports/documentation
+
+    Not all combinations of parameters and underlying assets are valid, bad combinations will return an error.
+    """
+
+    code: str = Field(
+        description="""
+            CFTC series code.  Use search_cot() to find the code.
+            Codes not listed in the curated list, but are published by on the Nasdaq Data Link website, are valid.
+            Certain symbols, such as "ES=F", or exact names are also valid.
+            Default report is: S&P 500 Consolidated (CME))
+            """,
+        default="13874P",
+    )
+    data_type: Optional[Literal["F", "FO", "CITS"]] = Field(
+        description="""
+            The type of data to reuturn. Default is "FO".
+
+            F = Futures only
+
+            FO = Futures and Options
+
+            CITS = Commodity Index Trader Supplemental. Only valid for commodities.
+        """,
+        default="FO",
+    )
+    legacy_format: Optional[bool] = Field(
+        description="Returns the legacy format of report. Default is False.",
+        default=False,
+    )
+    report_type: Optional[Literal["ALL", "CHG", "OLD", "OTR"]] = Field(
+        description="""
+            The type of report to return. Default is "ALL".
+
+                ALL = All
+
+                CHG = Change in Positions
+
+                OLD = Old Crop Years
+
+                OTR = Other Crop Years
+        """,
+        default="ALL",
+    )
+    measure: Optional[Literal["CR", "NT", "OI", "CHG"]] = Field(
+        description="""
+            The measure to return. Default is None.
+
+            CR = Concentration Ratios
+
+            NT = Number of Traders
+
+            OI = Percent of Open Interest
+
+            CHG = Change in Positions. Only valid when data_type is "CITS".
+        """,
+        default=None,
+    )
+    start_date: Optional[dateType] = Field(
+        description="The start date of the time series. Defaults to all.", default=None
+    )
+    end_date: Optional[dateType] = Field(
+        description="The end date of the time series. Defaults to the most recent data.",
+        default=None,
+    )
+    transform: Optional[Literal["diff", "rdiff", "cumul", "normalize"]] = Field(
+        description="Transform the data as w/w difference, percent change, cumulative, or normalize.",
+        default=None,
+    )
+
+
+class QuandlCotData(Data):
+    """Quandl CFTC Commitment of Traders Reports data.
+
+    Returns
+    -------
+    List[Dict]
+        Columns in the response object will change according to the parameters and underlying asset.
+    """
+
+    @validator("date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return the datetime object from the date string"""
+
+        return datetime.strptime(v, "%Y-%m-%d").date()
+
+
+class QuandlCotFetcher(Fetcher[QuandlCotQueryParams, List[QuandlCotData]]):
+    """Quandl CFTC Commitment of Traders Reports Fetcher."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> QuandlCotQueryParams:
+        return QuandlCotQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: QuandlCotQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        api_key = credentials.get("quandl_api_key") if credentials else ""
+
+        # The "code" can be an exact name, a symbol, or a CFTC series code.
+        series_id: str = ""
+        series_ids = pd.DataFrame(CFTC).transpose().reset_index(drop=True)
+        series_ids.columns = series_ids.columns.str.lower()
+
+        if query.code in series_ids["code"].values:
+            series_id = query.code
+
+        if query.code not in series_ids["code"].values:
+            if query.code in series_ids["symbol"].values:
+                series_id = series_ids.loc[
+                    series_ids["symbol"] == query.code, "code"
+                ].values[0]
+            if query.code in series_ids["name"].values:
+                series_id = series_ids.loc[
+                    series_ids["name"] == query.code, "code"
+                ].values[0]
+            # Allows for strings not found in the curated list.
+            if (
+                query.code not in series_ids["code"].values
+                and query.code not in series_ids["symbol"].values
+                and query.code not in series_ids["name"].values
+            ):
+                series_id = query.code
+
+        # The "quandl_code" gets parsed conditionally for the parameters.
+        quandl_code = f"CFTC/{series_id}"
+
+        if query.data_type:
+            quandl_code = f"{quandl_code}_{query.data_type}"
+
+        if query.legacy_format is False and query.data_type != "CITS":
+            quandl_code = f"{quandl_code}_L"
+
+        if query.report_type:
+            quandl_code = f"{quandl_code}_{query.report_type}"
+
+        if query.measure is not None:
+            quandl_code = f"{quandl_code}_{query.measure}"
+
+        try:
+            data = quandl.get(
+                quandl_code,
+                start_date=query.start_date,
+                end_date=query.end_date,
+                transform=query.transform,
+                api_key=api_key,
+            ).reset_index()
+            data.columns = [
+                to_snake_case(c)
+                .replace(" ", "")
+                .replace("-", "")
+                .replace("%", "_%_")
+                .replace("o_i", "oi")
+                .replace(";", "")
+                for c in data.columns
+            ]
+            data["date"] = data["date"].astype(str)
+            return data.to_dict("records")
+
+        except Exception as e:
+            raise RuntimeError(e)
+
+    @staticmethod
+    def transform_data(
+        data: List[Dict],
+    ) -> List[QuandlCotData]:
+        return [QuandlCotData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/models/cot_search.py b/openbb_sdk/providers/quandl/openbb_quandl/models/cot_search.py
new file mode 100644
index 00000000000..805c45b90f5
--- /dev/null
+++ b/openbb_sdk/providers/quandl/openbb_quandl/models/cot_search.py
@@ -0,0 +1,58 @@
+"""CFTC Commitment of Traders Reports Search fetcher."""
+
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.cot_search import (
+    CotSearchData,
+    CotSearchQueryParams,
+)
+
+from openbb_quandl.utils.series_ids import CFTC
+
+
+class QuandlCotSearchQueryParams(CotSearchQueryParams):
+    """CFTC Commitment of Traders Reports Search query parameters.
+
+    Source: https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports/documentation
+    """
+
+
+class QuandlCotSearchData(CotSearchData):
+    """Quandl CFTC Commitment of Traders Reports Search data."""
+
+
+class QuandlCotSearchFetcher(Fetcher[CotSearchQueryParams, List[QuandlCotSearchData]]):
+    """Quandl CFTC Commitment of Traders Reports Search Fetcher."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> QuandlCotSearchQueryParams:
+        return QuandlCotSearchQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: QuandlCotSearchQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any
+    ) -> List[Dict]:
+        """Search a curated list of CFTC Commitment of Traders Reports."""
+        query_string = query.query  # noqa
+        available_cot = pd.DataFrame(CFTC).transpose()
+        available_cot.columns = available_cot.columns.str.lower()
+        return (
+            available_cot.query(
+                "name.str.contains(@query_string, case=False)"
+                "| category.str.contains(@query_string, case=False)"
+                "| subcategory.str.contains(@query_string, case=False)"
+                "| symbol.str.contains(@query_string, case=False)"
+            )
+            .reset_index(drop=True)
+            .to_dict("records")
+        )
+
+    @staticmethod
+    def transform_data(
+        data: List[Dict],
+    ) -> List[QuandlCotSearchData]:
+        return [QuandlCotSearchData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/models/sp500_multiples.py b/openbb_sdk/providers/quandl/openbb_quandl/models/sp500_multiples.py
new file mode 100644
index 00000000000..5354c585d4c
--- /dev/null
+++ b/openbb_sdk/providers/quandl/openbb_quandl/models/sp500_multiples.py
@@ -0,0 +1,69 @@
+"""Quandl SP500 Multiples Fetcher."""
+
+from typing import Any, Dict, List, Optional
+
+import quandl
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.sp500_multiples import (
+    SP500MultiplesData,
+    SP500MultiplesQueryParams,
+)
+
+from openbb_quandl.utils.series_ids import SP500MULTIPLES
+
+
+class QuandlSP500MultiplesQueryParams(SP500MultiplesQueryParams):
+    """SP500 Multiples query."""
+
+
+class QuandlSP500MultiplesData(SP500MultiplesData):
+    """SP500 Multiples data."""
+
+
+class QuandlSP500MultiplesFetcher(
+    Fetcher[SP500MultiplesQueryParams, SP500MultiplesData]
+):
+    """Quandl SP500 Multiples Fetcher."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> QuandlSP500MultiplesQueryParams:
+        return QuandlSP500MultiplesQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: QuandlSP500MultiplesQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any
+    ) -> List[QuandlSP500MultiplesData]:
+        """Gets the raw Quandl Data."""
+
+        api_key = credentials.get("quandl_api_key") if credentials else ""
+
+        if "Year" in query.series_name:
+            query.collapse = "annual"
+        if "Quarter" in query.series_name:
+            query.collapse = "quarterly"
+
+        data = (
+            quandl.get(
+                SP500MULTIPLES[query.series_name],
+                start_date=query.start_date,
+                end_date=query.end_date,
+                collapse=query.collapse,
+                transform=query.transform,
+                api_key=api_key,
+                **kwargs,
+            )
+            .reset_index()
+            .rename(columns={"Date": "date", "Value": "value"})
+        )
+        data["date"] = data["date"].dt.strftime("%Y-%m-%d")
+
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: List[Dict],
+    ) -> List[QuandlSP500MultiplesData]:
+        """Parse data into the QuandlSP500MultiplesData format."""
+        return [QuandlSP500MultiplesData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/utils/__init__.py b/openbb_sdk/providers/quandl/openbb_quandl/utils/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/openbb_sdk/providers/quandl/openbb_quandl/utils/series_ids.py b/openbb_sdk/providers/quandl/openbb_quandl/utils/series_ids.py
new file mode 100644
index 00000000000..802dbdba6a1
--- /dev/null
+++ b/openbb_sdk/providers/quandl/openbb_quandl/utils/series_ids.py
@@ -0,0 +1,1044 @@
+"""Series ID Dictionaries for Quandl Provider."""
+
+SP500MULTIPLES = {
+    "Shiller PE Ratio by Month": "MULTPL/SHILLER_PE_RATIO_MONTH",
+    "Shiller PE Ratio by Year": "MULTPL/SHILLER_PE_RATIO_YEAR",
+    "PE Ratio by Year": "MULTPL/SP500_PE_RATIO_YEAR",
+    "PE Ratio by Month": "MULTPL/SP500_PE_RATIO_MONTH",
+    "Dividend by Year": "MULTPL/SP500_DIV_YEAR",
+    "Dividend by Month": "MULTPL/SP500_DIV_MONTH",
+    "Dividend Growth by Quarter": "MULTPL/SP500_DIV_GROWTH_QUARTER",
+    "Dividend Growth by Year": "MULTPL/SP500_DIV_GROWTH_YEAR",
+    "Dividend Yield by Year": "MULTPL/SP500_DIV_YIELD_YEAR",
+    "Dividend Yield by Month": "MULTPL/SP500_DIV_YIELD_MONTH",
+    "Earnings by Year": "MULTPL/SP500_EARNINGS_YEAR",
+    "Earnings by Month": "MULTPL/SP500_EARNINGS_MONTH",
+    "Earnings Growth by Year": "MULTPL/SP500_EARNINGS_GROWTH_YEAR",
+    "Earnings Growth by Quarter": "MULTPL/SP500_EARNINGS_GROWTH_QUARTER",
+    "Real Earnings Growth by Year": "MULTPL/SP500_REAL_EARNINGS_GROWTH_YEAR",
+    "Real Earnings Growth by Quarter": "MULTPL/SP500_REAL_EARNINGS_GROWTH_QUARTER",
+    "Earnings Yield by Year": "MULTPL/SP500_EARNINGS_YIELD_YEAR",
+    "Earnings Yield by Month": "MULTPL/SP500_EARNINGS_YIELD_MONTH",
+    "Real Price by Year": "MULTPL/SP500_REAL_PRICE_YEAR",
+    "Real Price by Month": "MULTPL/SP500_REAL_PRICE_MONTH",
+    "Inflation Adjusted Price by Year": "MULTPL/SP500_INFLADJ_YEAR",
+    "Inflation Adjusted Price by Month": "MULTPL/SP500_INFLADJ_MONTH",
+    "Sales by Year": "MULTPL/SP500_SALES_YEAR",
+    "Sales by Quarter": "MULTPL/SP500_SALES_QUARTER",
+    "Sales Growth by Year": "MULTPL/SP500_SALES_GROWTH_YEAR",
+    "Sales Growth by Quarter": "MULTPL/SP500_SALES_GROWTH_Quarter",
+    "Real Sales by Year": "MULTPL/SP500_REAL_SALES_YEAR",
+    "Real Sales by Quarter": "MULTPL/SP500_REAL_SALES_QUARTER",
+    "Real Sales Growth by Year": "MULTPL/SP500_REAL_SALES_GROWTH_YEAR",
+    "Real Sales Growth by Quarter": "MULTPL/SP500_REAL_SALES_GROWTH_QUARTER",
+    "Price to Sales Ratio by Year": "MULTPL/SP500_PSR_YEAR",
+    "Price to Sales Ratio by Quarter": "MULTPL/SP500_PSR_QUARTER",
+    "Price to Book Value Ratio by Year": "MULTPL/SP500_PBV_RATIO_YEAR",
+    "Price to Book Value Ratio by Quarter": "MULTPL/SP500_PBV_RATIO_QUARTER",
+    "Book Value per Share by Year": "MULTPL/SP500_BVPS_YEAR",
+    "Book Value per Share by Quarter": "MULTPL/SP500_BVPS_QUARTER",
+}
+
+
+CFTC = {
+    "098662": {
+        "Name": "USD Index (ICUS)",
+        "Category": "Currencies",
+        "Subcategory": "US Dollar Index",
+        "Units": "U.S. Dollar Index x $1000",
+        "Code": "098662",
+        "Symbol": "DX=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=098662",
+        "Specs": "https://www.theice.com/products/194/US-Dollar-Index-Futures",
+    },
+    "045601": {
+        "Name": "Fed Funds (CBT)",
+        "Category": "Interest",
+        "Subcategory": "Treasuries",
+        "Units": "Contracts of $5,000,000",
+        "Code": "045601",
+        "Symbol": "ZQ=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=045601",
+        "Specs": "https://www.cmegroup.com/markets/interest-rates/stirs/30-day-federal-fund.contractSpecs.html",
+    },
+    "020604": {
+        "Name": "Ultra US Treasury Bond (CBT)",
+        "Category": "Interest",
+        "Subcategory": "Treasuries",
+        "Units": "Contracts of $100,000",
+        "Code": "020604",
+        "Symbol": "UB=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=020604",
+        "Specs": "https://www.cmegroup.com/markets/interest-rates/us-treasury/ultra-t-bond.contractSpecs.options.html",
+    },
+    "042601": {
+        "Name": "Two-Year Treasury Note Futures (CBT)",
+        "Category": "Interest",
+        "Subcategory": "Treasuries",
+        "Units": "Contracts of $200,000 Face Value",
+        "Code": "042601",
+        "Symbol": "ZT=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=042601",
+        "Specs": "https://www.cmegroup.com/markets/interest-rates/us-treasury/2-year-us-treasury-note.contractSpecs.html",
+    },
+    "044601": {
+        "Name": "Five-Year Treasury Note Futures (CBT)",
+        "Category": "Interest",
+        "Subcategory": "Treasuries",
+        "Units": "Contracts of $100,000 Face Value",
+        "Code": "044601",
+        "Symbol": "ZF=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=044601",
+        "Specs": "https://www.cmegroup.com/markets/interest-rates/us-treasury/5-year-us-treasury-note.contractSpecs.html",
+    },
+    "043602": {
+        "Name": "Ten-Year Treasury Note Futures (CBT)",
+        "Category": "Interest",
+        "Subcategory": "Treasuries",
+        "Units": "Contracts of $100,000 Face Value",
+        "Code": "043602",
+        "Symbol": "ZN=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=043602",
+        "Specs": "https://www.cmegroup.com/markets/interest-rates/us-treasury/10-year-us-treasury-note.contractSpecs.html",  # noqa
+    },
+    "043607": {
+        "Name": "Ultra Ten-Year US Treasury Note (CBT)",
+        "Category": "Interest",
+        "Subcategory": "Treasuries",
+        "Units": "Contracts of $100,000 Face Value",
+        "Code": "043607",
+        "Symbol": "TN=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=043607",
+        "Specs": "https://www.cmegroup.com/markets/interest-rates/us-treasury/ultra-10-year-us-treasury-note.contractSpecs.html",  # noqa
+    },
+    "13874P": {
+        "Name": "S&P 500 Consolidated (CME)",
+        "Category": "Index",
+        "Subcategory": "S&P 500",
+        "Units": "S&P 500 Index X $250",
+        "Code": "13874P",
+        "Symbol": "^GSPC",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=13874P",
+        "Specs": "https://www.cmegroup.com/trading/equity-index/us-index/sp-index-futures-and-options.html",
+    },
+    "13874N": {
+        "Name": "S&P 500 Total Return Index (CME)",
+        "Category": "Index",
+        "Subcategory": "S&P 500",
+        "Units": "S&P 500 Index X $25",
+        "Code": "13874N",
+        "Symbol": "^SP500TR",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=13874N",
+        "Specs": "https://www.cmegroup.com/markets/equities/sp/sp-500-total-return.contractSpecs.html",
+    },
+    "13874W": {
+        "Name": "AIR S&P 500 Total Return Index (CME)",
+        "Category": "Index",
+        "Subcategory": "S&P 500",
+        "Units": "AIR S&P 500 Index X $25",
+        "Code": "13874W",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=13874W",
+        "Specs": "https://www.cmegroup.com/markets/equities/sp/adjusted-interest-rate-sp500-total-return.contractSpecs.html",  # noqa
+    },
+    "13874A": {
+        "Name": "E-Mini S&P 500 Index (CME)",
+        "Category": "Index",
+        "Subcategory": "S&P 500",
+        "Units": "S&P 500 Index X $50",
+        "Code": "13874A",
+        "Symbol": "ES=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=13874A",
+        "Specs": "https://www.cmegroup.com/markets/equities/sp/e-mini-sandp500.contractSpecs.html",
+    },
+    "13874U": {
+        "Name": "Micro E-Mini S&P 500 Index (CME)",
+        "Category": "Index",
+        "Subcategory": "S&P 500",
+        "Units": "S&P 500 Index X $5",
+        "Code": "13874U",
+        "Symbol": "MES=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=13874U",
+        "Specs": "https://www.cmegroup.com/markets/equities/sp/e-mini-sandp500.contractSpecs.html",
+    },
+    "20974P": {
+        "Name": "NASDAQ 100 Consolidated (CME)",
+        "Category": "Index",
+        "Subcategory": "NASDAQ",
+        "Units": "NASDAQ 100 Index X $100",
+        "Code": "20974P",
+        "Symbol": "^NDX",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=20974P",
+        "Specs": "https://www.cmegroup.com/trading/equity-index/nasdaq-index-futures-and-options.html",
+    },
+    "209742": {
+        "Name": "E-Mini NASDAQ 100 Index (CME)",
+        "Category": "Index",
+        "Subcategory": "NASDAQ",
+        "Units": "NASDAQ 100 Index X $20",
+        "Code": "209742",
+        "Symbol": "NQ=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=209742",
+        "Specs": "https://www.cmegroup.com/markets/equities/nasdaq/e-mini-nasdaq-100.contractSpecs.html",
+    },
+    "209747": {
+        "Name": "Micro E-Mini NASDAQ 100 Index (CME)",
+        "Category": "Index",
+        "Subcategory": "NASDAQ",
+        "Units": "NASDAQ 100 Index X $2",
+        "Code": "209747",
+        "Symbol": "MNQ=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=209747",
+        "Specs": "https://www.cmegroup.com/markets/equities/nasdaq/micro-e-mini-nasdaq-100.contractSpecs.html",
+    },
+    "12460P": {
+        "Name": "DJIA Consolidated (CBT)",
+        "Category": "Index",
+        "Subcategory": "Dow Jones",
+        "Units": "Dow Jones Index X $10",
+        "Code": "12460P",
+        "Symbol": "^DJI",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=12460P",
+        "Specs": "https://www.cmegroup.com/markets/products.html#assetClass=4&search=dow%20jones",
+    },
+    "124603": {
+        "Name": "E-Mini Dow Jones (CBT)",
+        "Category": "Index",
+        "Subcategory": "Dow Jones",
+        "Units": "Dow Jones Index X $5",
+        "Code": "124603",
+        "Symbol": "YM=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=124603",
+        "Specs": "https://www.cmegroup.com/markets/equities/dow-jones/e-mini-dow.contractSpecs.html",
+    },
+    "124606": {
+        "Name": "Dow Jones U.S. Real Estate Index (CBT)",
+        "Category": "Index",
+        "Subcategory": "Dow Jones",
+        "Units": "DJ US Real Estate Index X $100",
+        "Code": "124606",
+        "Symbol": "RX=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=124606",
+        "Specs": "https://www.cmegroup.com/markets/equities/dow-jones/dow-jones-rei.contractSpecs.html",
+    },
+    "239742": {
+        "Name": "E-Mini Russell 2000 Index (CME)",
+        "Category": "Index",
+        "Subcategory": "Russell",
+        "Units": "Russell 2000 Index X $50",
+        "Code": "239742",
+        "Symbol": "RTY=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=239742",
+        "Specs": "https://www.cmegroup.com/markets/equities/russell/e-mini-russell-2000.contractSpecs.html",
+    },
+    "239744": {
+        "Name": "E-Mini Russell 1000 Value Index (CME)",
+        "Category": "Index",
+        "Subcategory": "Russell",
+        "Units": "Russell 1000 Value Index X $50",
+        "Code": "239744",
+        "Symbol": "RSV=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=239744",
+        "Specs": "https://www.cmegroup.com/markets/equities/russell/e-mini-russell-1000-value-index.contractSpecs.html",
+    },
+    "1170E1": {
+        "Name": "VIX Futures (CBOE)",
+        "Category": "Index",
+        "Subcategory": "VIX",
+        "Units": "VIX Index X $1000",
+        "Code": "1170E1",
+        "Symbol": "^VIX",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=1170E1",
+        "Specs": "https://www.cboe.com/tradable_products/vix/vix_futures/specifications/",
+    },
+    "221602": {
+        "Name": "Bloomberg Commodity Index (CBT)",
+        "Category": "Index",
+        "Subcategory": "Commodities",
+        "Units": "Index X $100",
+        "Code": "221602",
+        "Symbol": "AW=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=221602",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/commodity-indices/bloomberg-commodity-index.contractSpecs.html",  # noqa
+    },
+    "0233AN": {
+        "Name": "Michon Financial Index",
+        "Category": "Index",
+        "Subcategory": "Commodities",
+        "Units": "Contract size: 2500 MMBTus",
+        "Code": "0233AN",
+        "Symbol": "NGT=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=0233AN",
+        "Specs": "https://www.theice.com/products/6590188/Michcon-Index-Future",
+    },
+    "02339Q": {
+        "Name": "Chicago Citygate Index",
+        "Category": "Energy",
+        "Subcategory": "Natural Gas",
+        "Units": "Contract size: 2500 MMBTus",
+        "Code": "02339Q",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=02339Q",
+        "Specs": "https://www.theice.com/products/6590179/Chicago-Index-Future",
+    },
+    "02339U": {
+        "Name": "CIG Rockies Basis",
+        "Category": "Energy",
+        "Subcategory": "Natural Gas",
+        "Units": "Contract size: 2500 MMBTus",
+        "Code": "02339U",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=02339U",
+        "Specs": "https://www.theice.com/products/6590129/CIG-Rockies-Basis-Future",
+    },
+    "0233A2": {
+        "Name": "DOMINION SOUTH POINT",
+        "Category": "Energy",
+        "Subcategory": "Natural Gas",
+        "Units": "Contract size: 2500 MMBTus",
+        "Code": "0233A2",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=0233A2",
+        "Specs": "https://www.theice.com/products/6590181/Eastern-Gas-South-Index-Future",
+    },
+    "244041": {
+        "Name": "MSCI EAFE (ICUS)",
+        "Category": "Index",
+        "Subcategory": "MSCI",
+        "Units": "MSCI EAFE Index Level X $50 USD",
+        "Code": "244041",
+        "Symbol": "MFS=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=244041",
+        "Specs": "https://www.theice.com/products/31196848/MSCI-EAFE-Index-Future",
+    },
+    "244042": {
+        "Name": "MSCI EM Index (ICUS)",
+        "Category": "Index",
+        "Subcategory": "MSCI",
+        "Units": "MSCI Emerging Markets Index X $50 USD",
+        "Code": "244042",
+        "Symbol": "MME=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=244042",
+        "Specs": "https://www.theice.com/products/31196851/MSCI-Emerging-Markets-Index-Future",
+    },
+    "0063DA": {
+        "Name": "PA Solar Alternative Energy Credit Future (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Renewables",
+        "Units": "10 MWh representing 10 Qualifying SRECs",
+        "Code": "0063DA",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=0063DA",
+        "Specs": "https://www.theice.com/products/65898879/Pennsylvania-Solar-Alternative-Energy-Credit-Future",
+    },
+    "075651": {
+        "Name": "Palladium Futures (NYME)",
+        "Category": "Metals",
+        "Subcategory": "Palladium",
+        "Units": "Contracts of 100 Troy Ounces",
+        "Code": "075651",
+        "Symbol": "PA=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=075651",
+        "Specs": "https://www.cmegroup.com/trading/metals/precious/palladium_contractSpecs_futures.html",
+    },
+    "076651": {
+        "Name": "Platinum Futures (NYME)",
+        "Category": "Metals",
+        "Subcategory": "Platinum",
+        "Units": "Contracts of 50 Troy Ounces",
+        "Code": "076651",
+        "Symbol": "PL=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=076651",
+        "Specs": "https://www.cmegroup.com/trading/metals/precious/platinum_contractSpecs_futures.html",
+    },
+    "085692": {
+        "Name": "Copper #1 Futures (CMX)",
+        "Category": "Metals",
+        "Subcategory": "Copper",
+        "Units": "Contracts of 25,000 pounds",
+        "Code": "085692",
+        "Symbol": "HG=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=085692",
+        "Specs": "https://www.cmegroup.com/markets/metals/base/copper.contractSpecs.html",
+    },
+    "191693": {
+        "Name": "Aluminum MWP Futures (CMX)",
+        "Category": "Metals",
+        "Subcategory": "Aluminum",
+        "Units": "Contracts of 25 Metric Tonnes (55,116 pounds)",
+        "Code": "191693",
+        "Symbol": "ALI=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=191693",
+        "Specs": "https://www.cmegroup.com/markets/metals/base/aluminum.contractSpecs.html",
+    },
+    "088691": {
+        "Name": "Gold Futures (CMX)",
+        "Category": "Metals",
+        "Subcategory": "Gold",
+        "Units": "Contracts of 100 Troy Ounces",
+        "Code": "088691",
+        "Symbol": "GC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=088691",
+        "Specs": "https://www.cmegroup.com/markets/metals/precious/gold.contractSpecs.html",
+    },
+    "088695": {
+        "Name": "Micro Gold Futures (CMX)",
+        "Category": "Metals",
+        "Subcategory": "Gold",
+        "Units": "Contracts of 10 Troy Ounces",
+        "Code": "088695",
+        "Symbol": "MGC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=088695",
+        "Specs": "https://www.cmegroup.com/markets/metals/precious/e-micro-gold.contractSpecs.html",
+    },
+    "084691": {
+        "Name": "Silver Futures (CMX)",
+        "Category": "Metals",
+        "Subcategory": "Silver",
+        "Units": "Contracts of 5,000 Troy Ounces",
+        "Code": "084691",
+        "Symbol": "SI=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=084691",
+        "Specs": "https://www.cmegroup.com/markets/metals/precious/silver.contractSpecs.html",
+    },
+    "00665T": {
+        "Name": "Mini-Silver Futures (ICUS)",
+        "Category": "Metals",
+        "Subcategory": "Silver",
+        "Units": "Contracts of 1,000 Troy Ounces",
+        "Code": "00665T",
+        "Symbol": "YI=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=00665T",
+        "Specs": "https://www.theice.com/products/31500923/Mini-Silver-Future",
+    },
+    "073732": {
+        "Name": "Cocoa Futures (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "Cocoa",
+        "Units": "Contracts of 10 Metric Tonnes",
+        "Code": "073732",
+        "Symbol": "CC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=073732",
+        "Specs": "https://www.theice.com/products/7/Cocoa-Futures",
+    },
+    "135731": {
+        "Name": "Canola Futures (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "Canola",
+        "Units": "Contracts of 20 Metric Tonnes",
+        "Code": "135731",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=135731",
+        "Specs": "https://www.theice.com/products/251/Canola-Futures",
+    },
+    "058643": {
+        "Name": "Random Length Lumber Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Lumber",
+        "Units": "Contracts of 110,000 Board Feet",
+        "Code": "058643",
+        "Symbol": "LBS=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=058643",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/lumber-and-softs/random-length-lumber.contractSpecs.html",
+    },
+    "033661": {
+        "Name": "Cotton #2 Futures (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "Cotton",
+        "Units": "Contracts of 50,000 pounds",
+        "Code": "033661",
+        "Symbol": "CT=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=033661",
+        "Specs": "https://www.theice.com/products/254/Cotton-No-2-Futures",
+    },
+    "040701": {
+        "Name": "Frozen Concentrated Orange Juice Futures (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "OJ",
+        "Units": "Contracts of 15,000 pounds",
+        "Code": "040701",
+        "Symbol": "OJ=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=040701",
+        "Specs": "https://www.theice.com/products/30/FCOJ-A-Futures",
+    },
+    "083731": {
+        "Name": "Coffee Futures (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "Coffee",
+        "Units": "Contracts of 37,500 pounds",
+        "Code": "083731",
+        "Symbol": "KC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=083731",
+        "Specs": "https://www.theice.com/products/15/Coffee-C-Futures",
+    },
+    "083736": {
+        "Name": "Coffee Calendar Spread Options (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "Coffee",
+        "Units": "Contracts of 37,500 pounds",
+        "Code": "083736",
+        "Symbol": "KC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=083736",
+        "Specs": "https://www.theice.com/products/67445363/Coffee-C-1-Month-Calendar-Spread-Option",
+    },
+    "080732": {
+        "Name": "Sugar #11 Futures (ICUS)",
+        "Category": "Agriculture",
+        "Subcategory": "Sugar",
+        "Units": "Contracts of 112,000 pounds",
+        "Code": "080732",
+        "Symbol": "SF=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=080732",
+        "Specs": "https://www.theice.com/products/23/Sugar-No-11-Futures",
+    },
+    "052645": {
+        "Name": "Dry Whey Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Dairy",
+        "Units": "Contracts of 44,000 pounds",
+        "Code": "052645",
+        "Symbol": "DY=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=052645",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/dairy/dry-whey.contractSpecs.html",
+    },
+    "005602": {
+        "Name": "Soybeans Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Soy",
+        "Units": "Contracts of 5,000 bushels",
+        "Code": "005602",
+        "Symbol": "ZS=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=005602",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/oilseeds/soybean.contractSpecs.html",
+    },
+    "005603": {
+        "Name": "Mini Soybeans Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Soy",
+        "Units": "Contracts of 1,000 bushels",
+        "Code": "005603",
+        "Symbol": "XK=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=005603",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/oilseeds/mini-sized-soybean.contractSpecs.html",
+    },
+    "026603": {
+        "Name": "Soybean Meal Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Soy",
+        "Units": "Contracts of 100 short tons",
+        "Code": "026603",
+        "Symbol": "ZM=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=026603",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/oilseeds/soybean-meal.contractSpecs.html",
+    },
+    "256741": {
+        "Name": "S&P GSCI Commodity Index Futures (CBT)",
+        "Category": "Index",
+        "Subcategory": "Commodities",
+        "Units": "GSCI X $250",
+        "Code": "256741",
+        "Symbol": "GD=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=256741",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/commodity-indices/gsci.contractSpecs.html",
+    },
+    "007601": {
+        "Name": "Soybean Oil Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Soy",
+        "Units": "Contracts of 60,000 pounds",
+        "Code": "007601",
+        "Symbol": "ZL=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=007601",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/oilseeds/soybean-oil.contractSpecs.html",
+    },
+    "001612": {
+        "Name": "Commitment of Traders - KC HRW Wheat Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Grains",
+        "Units": "Contracts of 5,000 Bushels",
+        "Code": "001612",
+        "Symbol": "KE=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=001612",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/grains/kc-wheat.contractSpecs.html",
+    },
+    "001626": {
+        "Name": "Commitment of Traders - KC HRSpring Wheat Futures (MGE)",
+        "Category": "Agriculture",
+        "Subcategory": "Grains",
+        "Units": "Contracts of 5,000 Bushels",
+        "Code": "001626",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=001626",
+        "Specs": "https://www.mgex.com/quotes.html?j1_module=futureDetail&j1_symbol=MW%2A1&j1_region=US&j1_selected=futureProfile",  # noqa
+    },
+    "001602": {
+        "Name": "Commitment of Traders - Chicago SRW Wheat Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Grains",
+        "Units": "Contracts of 5,000 Bushels",
+        "Code": "001602",
+        "Symbol": "ZW=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=001602",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/grains/wheat.contractSpecs.html",
+    },
+    "004603": {
+        "Name": "Oats Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Grains",
+        "Units": "Contracts of 5,000 Bushels",
+        "Code": "004603",
+        "Symbol": "ZO=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=004603",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/grains/oats.contractSpecs.html",
+    },
+    "039601": {
+        "Name": "Rought Rice Futures (CBT)",
+        "Category": "Agriculture",
+        "Subcategory": "Grains",
+        "Units": "Contracts of 200,000 pounds",
+        "Code": "039601",
+        "Symbol": "ZR=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=039601",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/grains/rough-rice.contractSpecs.html",
+    },
+    "054642": {
+        "Name": "Lean Hog Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Meats",
+        "Units": "Contracts of 40,000 Pounds",
+        "Code": "054642",
+        "Symbol": "HE=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=054642",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/livestock/lean-hogs.contractSpecs.html",
+    },
+    "057642": {
+        "Name": "Live Cattle (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Meats",
+        "Units": "Contracts of 40,000 Pounds",
+        "Code": "057642",
+        "Symbol": "LE=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=057642",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/livestock/live-cattle.contractSpecs.html",
+    },
+    "061641": {
+        "Name": "Feeder Cattle (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Meats",
+        "Units": "Contracts of 50,000 Pounds",
+        "Code": "061641",
+        "Symbol": "GF=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=061641",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/livestock/feeder-cattle.contractSpecs.html",
+    },
+    "063642": {
+        "Name": "Cash-Settled Cheese Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Dairy",
+        "Units": "Contracts of 20,000 Pounds",
+        "Code": "063642",
+        "Symbol": "CSC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/dairy/cheese.contractSpecs.html",
+    },
+    "052641": {
+        "Name": "Class III Milk Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Dairy",
+        "Units": "Contracts of 200,000 Pounds",
+        "Code": "052641",
+        "Symbol": "DC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=052641",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/dairy/class-iii-milk.contractSpecs.html",
+    },
+    "052644": {
+        "Name": "Class IV Milk Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Dairy",
+        "Units": "Contracts of 200,000 Pounds",
+        "Code": "052644",
+        "Symbol": "GDK=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=052644",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/dairy/class-iv-milk.contractSpecs.html",
+    },
+    "052642": {
+        "Name": "Non Fat Dry Milk Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Dairy",
+        "Units": "Contracts of 44,000 Pounds",
+        "Code": "052642",
+        "Symbol": "GNF=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=052642",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/dairy/nonfat-dry-milk.contractSpecs.html",
+    },
+    "050642": {
+        "Name": "Cash-Settled Butter (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Dairy",
+        "Units": "Contracts of 20,000 Pounds",
+        "Code": "050642",
+        "Symbol": "CB=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=050642",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/dairy/nonfat-dry-milk.contractSpecs.html",
+    },
+    "002602": {
+        "Name": "Corn Futures (CME)",
+        "Category": "Agriculture",
+        "Subcategory": "Corn",
+        "Units": "Contracts of 5,000 Bushels",
+        "Code": "002602",
+        "Symbol": "ZC=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=002602",
+        "Specs": "https://www.cmegroup.com/markets/agriculture/grains/corn.contractSpecs.futures.html",
+    },
+    "03565B": {
+        "Name": "Henry Hub Natural Gas Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Natural Gas",
+        "Units": "Contracts of 2,500 MMBTU's",
+        "Code": "03565B",
+        "Symbol": "NG=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=03565B",
+        "Specs": "https://www.cmegroup.com/markets/energy/natural-gas/natural-gas.contractSpecs.html",
+    },
+    "022651": {
+        "Name": "NY Harbor ULSD Heating Oil Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 42,000 Gallons",
+        "Code": "022651",
+        "Symbol": "HO=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=022651",
+        "Specs": "https://www.cmegroup.com/markets/energy/refined-products/heating-oil.contractSpecs.html",
+    },
+    "111659": {
+        "Name": "RBOB Gasoline Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 42,000 Gallons",
+        "Code": "111659",
+        "Symbol": "RB=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=111659",
+        "Specs": "https://www.cmegroup.com/markets/energy/refined-products/rbob-gasoline.contractSpecs.html",
+    },
+    "86665A": {
+        "Name": "Naphta Crack Spread Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 1,000 Barrels ",
+        "Code": "86665A",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=86665A",
+        "Specs": "https://www.cmegroup.com/markets/energy/refined-products/european-naphtha-crack-spread-swap.contractSpecs.html",  # noqa
+    },
+    "06665T": {
+        "Name": "Conway Propane Swap (OPIS) (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 42,000 Gallons",
+        "Code": "06665T",
+        "Symbol": "A8K",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06665T",
+        "Specs": "https://www.cmegroup.com/markets/energy/petrochemicals/conway-propane-opis-swap.contractSpecs.html",
+    },
+    "067A71": {
+        "Name": "WTI Midland (Argus) vs. WTI Trade Month Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "067A71",
+        "Symbol": "WTT",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=067A71",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/wti-midland-argus-vs-wti-trade-month.contractSpecs.html",  # noqa
+    },
+    "0676A5": {
+        "Name": "WTI Houston (Argus) vs. WTI Trade Month Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "0676A5",
+        "Symbol": "HTT",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=0676A5",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/wti-houston-argus-vs-wti-trade-month.contractSpecs.html",  # noqa
+    },
+    "06765A": {
+        "Name": "WTI Crude Oil Financial Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "06765A",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06765A",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/west-texas-intermediate-wti-crude-oil-calendar-swap-futures.contractSpecs.html",  # noqa
+    },
+    "067651": {
+        "Name": "WTI Physical Settlement Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "067651",
+        "Symbol": "CL=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=067651",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/light-sweet-crude.contractSpecs.html",
+    },
+    "06765T": {
+        "Name": "Brent Last Day Financial Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "06765T",
+        "Symbol": "BZ=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06765T",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/brent-crude-oil-last-day.contractSpecs.html",
+    },
+    "06765Z": {
+        "Name": "WTI-Brent Spread Option Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "06765Z",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06765Z",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/wti-brent-ice-bullet-swap-futures.contractSpecs.html",
+    },
+    "299741": {
+        "Name": "Euro FX/British Pound XRate Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "EUR/GBP",
+        "Units": "Contracts of EUR 125,000",
+        "Code": "299741",
+        "Symbol": "RP=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=299741",
+        "Specs": "https://www.cmegroup.com/markets/fx/cross-rates/euro-fx-british-pound.contractSpecs.html",
+    },
+    "097741": {
+        "Name": "Japanese Yen Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/JPY",
+        "Units": "Contracts of Contracts of JPY 12,500,000",
+        "Code": "097741",
+        "Symbol": "6J=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=097741",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/japanese-yen.contractSpecs.html",
+    },
+    "099741": {
+        "Name": "Euro FX Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/EUR",
+        "Units": "Contracts of EUR 125,000",
+        "Code": "099741",
+        "Symbol": "6E=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=099741",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/euro-fx.contractSpecs.html",
+    },
+    "090741": {
+        "Name": "Canadian Dollar Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/CAD",
+        "Units": "Contracts of CAD 100,000",
+        "Code": "090741",
+        "Symbol": "6C=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=090741",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/canadian-dollar.contractSpecs.html",
+    },
+    "096742": {
+        "Name": "British Pound Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/GBP",
+        "Units": "Contracts of GBP 62,500",
+        "Code": "096742",
+        "Symbol": "6B=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=096742",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/british-pound.contractSpecs.html",
+    },
+    "232741": {
+        "Name": "Australian Dollar Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/AUD",
+        "Units": "Contracts of AUD 100,000",
+        "Code": "232741",
+        "Symbol": "6A=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=232741",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/australian-dollar.contractSpecs.html",
+    },
+    "095741": {
+        "Name": "Mexican Peso Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/MXY",
+        "Units": "Contracts of 500,000 Mexican Pesos",
+        "Code": "095741",
+        "Symbol": "6M=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=095741",
+        "Specs": "https://www.cmegroup.com/markets/fx/emerging-market/mexican-peso.contractSpecs.html",
+    },
+    "112741": {
+        "Name": "New Zealand Dollar Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/NZD",
+        "Units": "Contracts of NZD 100,000",
+        "Code": "112741",
+        "Symbol": "6N=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=112741",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/new-zealand-dollar.contractSpecs.html",
+    },
+    "092741": {
+        "Name": "Swiss Franc Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/CHF",
+        "Units": "Contracts of CHF 125,000",
+        "Code": "092741",
+        "Symbol": "6S=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=092741",
+        "Specs": "https://www.cmegroup.com/markets/fx/g10/swiss-franc.contractSpecs.html",
+    },
+    "102741": {
+        "Name": "Brazilian Real Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/BRL",
+        "Units": "Contracts of BRL 100,000",
+        "Code": "102741",
+        "Symbol": "6L=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=102741",
+        "Specs": "https://www.cmegroup.com/markets/fx/emerging-market/brazilian-real.contractSpecs.html",
+    },
+    "122741": {
+        "Name": "South African Rand Futures (CME)",
+        "Category": "Currencies",
+        "Subcategory": "USD/ZAR",
+        "Units": "Contracts of ZAR 500,000",
+        "Code": "122741",
+        "Symbol": "6Z=F",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=122741",
+        "Specs": "https://www.cmegroup.com/markets/fx/emerging-market/south-african-rand.contractSpecs.html",
+    },
+    "021397": {
+        "Name": "Marine Fuel Oil 0.5% FOB USGC Futures (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "021397",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=021397",
+        "Specs": "https://www.theice.com/products/71085678/Fuel-Oil-Outright-Marine-Fuel-05-FOB-USGC-Barges-Platts-Future",  # noqa
+    },
+    "02141C": {
+        "Name": "Fuel Oil -3% USGC vs. 3.5% FOB RDAM (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Spread",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "02141B",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=02141C",
+        "Specs": "https://www.theice.com/products/6753390/Fuel-Oil-Diff-USGC-HSFO-Platts-vs-Fuel-Oil-35-FOB-Rotterdam-Barges-Platts-Future-in-bbls",  # noqa
+    },
+    "02141B": {
+        "Name": "USGC HSFO (Platts) Futures (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "02141B",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=02141B",
+        "Specs": "https://www.theice.com/products/6753543/Fuel-Oil-Outright-USGC-HSFO-Platts-Future",
+    },
+    "02141R": {
+        "Name": "USGC HSFO (Platts) vs. Brent 1st Line (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Spread",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "02141R",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=02141R",
+        "Specs": "https://www.theice.com/products/6753290/Fuel-Oil-Crack-USGC-HSFO-Platts-vs-Brent-1st-Line-Future",
+    },
+    "02165A": {
+        "Name": "Gulf #6 Fuel 3.0% Sulfur Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "02165A",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=02165A",
+        "Specs": "https://www.cmegroup.com/markets/energy/refined-products/gulf-coast-no-6-fuel-oil-30pct-sulfur-platts-swap.contractSpecs.html",  # noqa
+    },
+    "025608": {
+        "Name": "Ethanol T2 FOB Futures Including Duty (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 100 Cubic Meters (EUR)",
+        "Code": "025608",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=025608",
+        "Specs": "https://www.cmegroup.com/markets/energy/biofuels/ethanol-platts-t2-fob-rotterdam-including-duty-swap-futures.contractSpecs.html",  # noqa
+    },
+    "025651": {
+        "Name": "Ethanol Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 42,000 Gallons",
+        "Code": "025651",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=025651",
+        "Specs": "https://www.cmegroup.com/markets/energy/biofuels/new-york-ethanol-platts-swap.contractSpecs.html",
+    },
+    "03265J": {
+        "Name": "Mini European Naphtha CIF NWE (Platts) Futures (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Petroleum Products",
+        "Units": "Contracts of 100 Metric Tons",
+        "Code": "03265J",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=03265J",
+        "Specs": "https://www.cmegroup.com/markets/energy/refined-products/mini-european-naphtha-platts-cif-nwe-swap-futures.contractSpecs.html",  # noqa
+    },
+    "06739C": {
+        "Name": "Crude Diff Argus WCS vs. WTI 1st (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Crude Oil",
+        "Units": "Contracts of 42,000 Gallons",
+        "Code": "06739C",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06739C",
+        "Specs": "https://www.theice.com/products/67689141/Crude-Diff-Argus-WCS-Houston-Crude-Oil-Trade-Month-Future",
+    },
+    "067411": {
+        "Name": "Light Sweet WTI Futures (ICEU)",
+        "Category": "Energy",
+        "Subcategory": "Crude Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "067411",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=067411",
+        "Specs": "https://www.theice.com/products/213/WTI-Crude-Futures",
+    },
+    "06742T": {
+        "Name": "Crude Diff - ICE SW 1A Index Futures (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Crude Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "06742T",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06742T",
+        "Specs": "https://www.theice.com/products/31687075/Crude-Diff-ICE-SW-1a-Index-Future",
+    },
+    "06742G": {
+        "Name": "Crude Diff - ICE WCS 1A Index Futures (IFED)",
+        "Category": "Energy",
+        "Subcategory": "Crude Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "06742G",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06742G",
+        "Specs": "https://www.theice.com/products/27066814/Crude-Diff-ICE-WCS-1A-Index-Future",
+    },
+    "06765C": {
+        "Name": "Crude Oil Average Price Options Futres (NYM)",
+        "Category": "Energy",
+        "Subcategory": "Crude Oil",
+        "Units": "Contracts of 1,000 Barrels",
+        "Code": "06765C",
+        "Symbol": "",
+        "Permalink": "https://data.nasdaq.com/data/CFTC-commodity-futures-trading-commission-reports?keyword=06765C",
+        "Specs": "https://www.cmegroup.com/markets/energy/crude-oil/west-texas-intermediate-wti-crude-oil-calendar-swap-futures.contractSpecs.options.html#optionProductId=2767",  # noqa
+    },
+}
diff --git a/openbb_sdk/providers/quandl/poetry.lock b/openbb_sdk/providers/quandl/poetry.lock
new file mode 100644
index 00000000000..7e8a14e9d5d
--- /dev/null
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+    {file = "websockets-10.4.tar.gz", hash = "sha256:eef610b23933c54d5d921c92578ae5f89813438fded840c2e9809d378dc765d3"},
+]
+
+[[package]]
+name = "zipp"
+version = "3.16.2"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
+    {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.8"
+content-hash = "beb9403ccbf64a92b997c341935d6fc18aa9702093ed6a289585a58d035d513e"
diff --git a/openbb_sdk/providers/quandl/pyproject.toml b/openbb_sdk/providers/quandl/pyproject.toml
new file mode 100644
index 00000000000..d4c1eda8293
--- /dev/null
+++ b/openbb_sdk/providers/quandl/pyproject.toml
@@ -0,0 +1,19 @@
+[tool.poetry]
+name = "openbb-quandl"
+version = "0.1.0"
+description = ""
+authors = ["OpenBB Team <hello@openbb.co>"]
+readme = "README.md"
+packages = [{ include = "openbb_quandl" }]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+quandl = ">=3.7.0"
+openbb-core = { path = "../../sdk/core" }
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.plugins."openbb_provider_extension"]
+quandl = "openbb_quandl:quandl_provider"
diff --git a/openbb_sdk/providers/quandl/tests/.gitkeep b/openbb_sdk/providers/quandl/tests/.gitkeep
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/__init__.py b/openbb_sdk/providers/yfinance/openbb_yfinance/__init__.py
index e687e8ff01e..2a5181dc3ce 100644
--- a/openbb_sdk/providers/yfinance/openbb_yfinance/__init__.py
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/__init__.py
@@ -3,12 +3,19 @@
 
 from openbb_provider.abstract.provider import Provider
 
-from openbb_yfinance.models.crypto_eod import YFinanceCryptoEODFetcher
-from openbb_yfinance.models.forex_eod import YFinanceForexEODFetcher
+from openbb_yfinance.models.available_indices import YFinanceAvailableIndicesFetcher
+from openbb_yfinance.models.balance_sheet import YFinanceBalanceSheetFetcher
+from openbb_yfinance.models.cash_flow import YFinanceCashFlowStatementFetcher
+from openbb_yfinance.models.crypto_historical import YFinanceCryptoHistoricalFetcher
+from openbb_yfinance.models.forex_historical import YFinanceForexHistoricalFetcher
 from openbb_yfinance.models.futures_curve import YFinanceFuturesCurveFetcher
-from openbb_yfinance.models.futures_eod import YFinanceFuturesEODFetcher
-from openbb_yfinance.models.major_indices_eod import YFinanceMajorIndicesEODFetcher
-from openbb_yfinance.models.stock_eod import YFinanceStockEODFetcher
+from openbb_yfinance.models.futures_historical import YFinanceFuturesHistoricalFetcher
+from openbb_yfinance.models.income_statement import YFinanceIncomeStatementFetcher
+from openbb_yfinance.models.major_indices_historical import (
+    YFinanceMajorIndicesHistoricalFetcher,
+)
+from openbb_yfinance.models.stock_historical import YFinanceStockHistoricalFetcher
+from openbb_yfinance.models.stock_news import YFinanceStockNewsFetcher
 
 yfinance_provider = Provider(
     name="yfinance",
@@ -16,13 +23,17 @@ yfinance_provider = Provider(
     description="""Yahoo! Finance is a web-based platform that offers financial news,
     data, and tools for investors and individuals interested in tracking and analyzing
     financial markets and assets.""",
-    required_credentials=None,
     fetcher_dict={
-        "CryptoEOD": YFinanceCryptoEODFetcher,
-        "ForexEOD": YFinanceForexEODFetcher,
-        "MajorIndicesEOD": YFinanceMajorIndicesEODFetcher,
-        "StockEOD": YFinanceStockEODFetcher,
-        "FuturesEOD": YFinanceFuturesEODFetcher,
+        "CryptoHistorical": YFinanceCryptoHistoricalFetcher,
+        "ForexHistorical": YFinanceForexHistoricalFetcher,
+        "MajorIndicesHistorical": YFinanceMajorIndicesHistoricalFetcher,
+        "StockHistorical": YFinanceStockHistoricalFetcher,
+        "FuturesHistorical": YFinanceFuturesHistoricalFetcher,
         "FuturesCurve": YFinanceFuturesCurveFetcher,
+        "StockNews": YFinanceStockNewsFetcher,
+        "BalanceSheet": YFinanceBalanceSheetFetcher,
+        "CashFlowStatement": YFinanceCashFlowStatementFetcher,
+        "IncomeStatement": YFinanceIncomeStatementFetcher,
+        "AvailableIndices": YFinanceAvailableIndicesFetcher,
     },
 )
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/available_indices.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/available_indices.py
new file mode 100644
index 00000000000..690b2766305
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/available_indices.py
@@ -0,0 +1,58 @@
+"""Available Indices Fetcher for YFinance."""
+
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.available_indices import (
+    AvailableIndicesData,
+    AvailableIndicesQueryParams,
+)
+from pydantic import Field
+
+from openbb_yfinance.utils.references import INDICES
+
+
+class YFinanceAvailableIndicesQueryParams(AvailableIndicesQueryParams):
+    """Available Indices query for YFinance."""
+
+
+class YFinanceAvailableIndicesData(AvailableIndicesData):
+    """Available Indices data for YFinance."""
+
+    code: str = Field(
+        description="ID code for keying the index in the OpenBB Terminal."
+    )
+    symbol: str = Field(
+        description="yFinance ticker symbol for the index.", alias="ticker"
+    )
+
+
+class YFinanceAvailableIndicesFetcher(
+    Fetcher[
+        YFinanceAvailableIndicesQueryParams,
+        List[YFinanceAvailableIndicesData],
+    ]
+):
+    """Transform the query, extract and transform the data."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceAvailableIndicesQueryParams:
+        """Transform the query params."""
+        return YFinanceAvailableIndicesQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceAvailableIndicesQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[Dict]:
+        indices = pd.DataFrame(INDICES).transpose().reset_index()
+        indices.columns = ["code", "name", "ticker"]
+
+        return indices.to_dict("records")
+
+    @staticmethod
+    def transform_data(data: List[Dict]) -> List[YFinanceAvailableIndicesData]:
+        """Return the transformed data."""
+        return [YFinanceAvailableIndicesData(**d) for d in data]
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/balance_sheet.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/balance_sheet.py
new file mode 100644
index 00000000000..e547f929752
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/balance_sheet.py
@@ -0,0 +1,63 @@
+"""yfinance Balance Sheet Fetcher."""
+
+
+import json
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.balance_sheet import (
+    BalanceSheetData,
+    BalanceSheetQueryParams,
+)
+from pydantic import validator
+from yfinance import Ticker
+
+
+class YFinanceBalanceSheetQueryParams(BalanceSheetQueryParams):
+    """yfinance Balance Sheet QueryParams.
+
+    Source: https://finance.yahoo.com/
+    """
+
+
+class YFinanceBalanceSheetData(BalanceSheetData):
+    """yfinance Balance Sheet Data."""
+
+    # TODO: Standardize the fields
+
+    @validator("date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        return datetime.strptime(v, "%Y-%m-%d %H:%M:%S").date()
+
+
+class YFinanceBalanceSheetFetcher(
+    Fetcher[
+        YFinanceBalanceSheetQueryParams,
+        YFinanceBalanceSheetData,
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceBalanceSheetQueryParams:
+        return YFinanceBalanceSheetQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceBalanceSheetQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[YFinanceBalanceSheetData]:
+        query.period = "yearly" if query.period == "annually" else "quarterly"
+        data = Ticker(query.symbol).get_balance_sheet(
+            as_dict=True, pretty=False, freq=query.period
+        )
+        data = [{"date": str(key), **value} for key, value in data.items()]
+        data = json.loads(json.dumps(data))
+
+        return [YFinanceBalanceSheetData.parse_obj(d) for d in data]
+
+    @staticmethod
+    def transform_data(
+        data: List[YFinanceBalanceSheetData],
+    ) -> List[YFinanceBalanceSheetData]:
+        return data
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/cash_flow.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/cash_flow.py
new file mode 100644
index 00000000000..3d531aefd36
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/cash_flow.py
@@ -0,0 +1,63 @@
+"""yfinance Cash Flow Statement Fetcher."""
+
+
+import json
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.cash_flow import (
+    CashFlowStatementData,
+    CashFlowStatementQueryParams,
+)
+from pydantic import validator
+from yfinance import Ticker
+
+
+class YFinanceCashFlowStatementQueryParams(CashFlowStatementQueryParams):
+    """yfinance Cash Flow Statement QueryParams.
+
+    Source: https://finance.yahoo.com/
+    """
+
+
+class YFinanceCashFlowStatementData(CashFlowStatementData):
+    """yfinance Cash Flow Statement Data."""
+
+    # TODO: Standardize the fields
+
+    @validator("date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        return datetime.strptime(v, "%Y-%m-%d %H:%M:%S").date()
+
+
+class YFinanceCashFlowStatementFetcher(
+    Fetcher[
+        YFinanceCashFlowStatementQueryParams,
+        YFinanceCashFlowStatementData,
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceCashFlowStatementQueryParams:
+        return YFinanceCashFlowStatementQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceCashFlowStatementQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[YFinanceCashFlowStatementData]:
+        query.period = "yearly" if query.period == "annually" else "quarterly"
+        data = Ticker(query.symbol).get_cash_flow(
+            as_dict=True, pretty=False, freq=query.period
+        )
+        data = [{"date": str(key), **value} for key, value in data.items()]
+        data = json.loads(json.dumps(data))
+
+        return [YFinanceCashFlowStatementData.parse_obj(d) for d in data]
+
+    @staticmethod
+    def transform_data(
+        data: List[YFinanceCashFlowStatementData],
+    ) -> List[YFinanceCashFlowStatementData]:
+        return data
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/crypto_historical.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/crypto_historical.py
new file mode 100644
index 00000000000..1aa761d7f50
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/crypto_historical.py
@@ -0,0 +1,112 @@
+"""yfinance Crypto End of Day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.crypto_historical import (
+    CryptoHistoricalData,
+    CryptoHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, validator
+from yfinance import Ticker
+
+from openbb_yfinance.utils.references import INTERVALS, PERIODS
+
+
+class YFinanceCryptoHistoricalQueryParams(CryptoHistoricalQueryParams):
+    """YFinance Crypto End of Day Query.
+
+    Source: https://finance.yahoo.com/crypto/
+    """
+
+    interval: Optional[INTERVALS] = Field(default="1d", description="Data granularity.")
+    period: Optional[PERIODS] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("period", "")
+    )
+    prepost: bool = Field(
+        default=False, description="Include Pre and Post market data."
+    )
+    adjust: bool = Field(default=True, description="Adjust all the data automatically.")
+    back_adjust: bool = Field(
+        default=False, description="Back-adjusted data to mimic true historical prices."
+    )
+
+
+class YFinanceCryptoHistoricalData(CryptoHistoricalData):
+    """YFinance Crypto End of Day Data."""
+
+    @validator("Date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return datetime object from string."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
+
+
+class YFinanceCryptoHistoricalFetcher(
+    Fetcher[
+        YFinanceCryptoHistoricalQueryParams,
+        List[YFinanceCryptoHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the yfinance endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceCryptoHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        if params.get("period") is None:
+            transformed_params = params
+
+            now = datetime.now().date()
+            if params.get("start_date") is None:
+                transformed_params["start_date"] = now - relativedelta(years=1)
+
+            if params.get("end_date") is None:
+                transformed_params["end_date"] = now
+            return YFinanceCryptoHistoricalQueryParams(**transformed_params)
+
+        return YFinanceCryptoHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceCryptoHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the yfinance endpoint."""
+        if query.period:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                period=query.period,
+                actions=False,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                raise_errors=True,
+            )
+        else:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                start=query.start_date,
+                end=query.end_date,
+                actions=False,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                raise_errors=True,
+            )
+
+        data = data.reset_index()
+        data["Date"] = (
+            data["Date"].dt.tz_localize(None).dt.strftime("%Y-%m-%dT%H:%M:%S")
+        )
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[YFinanceCryptoHistoricalData]:
+        """Transform the data to the standard format."""
+        return [YFinanceCryptoHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/forex_historical.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/forex_historical.py
new file mode 100644
index 00000000000..24aef6c6b1f
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/forex_historical.py
@@ -0,0 +1,116 @@
+"""yfinance Forex End of Day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.forex_historical import (
+    ForexHistoricalData,
+    ForexHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, validator
+from yfinance import Ticker
+
+from openbb_yfinance.utils.references import INTERVALS, PERIODS
+
+
+class YFinanceForexHistoricalQueryParams(ForexHistoricalQueryParams):
+    """YFinance Forex End of Day Query.
+
+    Source: https://finance.yahoo.com/currencies/
+    """
+
+    interval: Optional[INTERVALS] = Field(default="1d", description="Data granularity.")
+    period: Optional[PERIODS] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("period", "")
+    )
+    prepost: bool = Field(
+        default=False, description="Include Pre and Post market data."
+    )
+    adjust: bool = Field(default=True, description="Adjust all the data automatically.")
+    back_adjust: bool = Field(
+        default=False, description="Back-adjusted data to mimic true historical prices."
+    )
+
+
+class YFinanceForexHistoricalData(ForexHistoricalData):
+    """YFinance Forex End of Day Data."""
+
+    @validator("Date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return datetime object from string."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
+
+
+class YFinanceForexHistoricalFetcher(
+    Fetcher[
+        YFinanceForexHistoricalQueryParams,
+        List[YFinanceForexHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the yfinance endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceForexHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        if params.get("period") is None:
+            transformed_params = params
+
+            now = datetime.now().date()
+            if params.get("start_date") is None:
+                transformed_params["start_date"] = now - relativedelta(years=1)
+
+            if params.get("end_date") is None:
+                transformed_params["end_date"] = now
+            return YFinanceForexHistoricalQueryParams(**transformed_params)
+
+        return YFinanceForexHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceForexHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the yfinance endpoint."""
+        query.symbol = f"{query.symbol}=X"
+
+        if query.period:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                period=query.period,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+
+        else:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                start=query.start_date,
+                end=query.end_date,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+
+        data = data.reset_index()
+        data["Date"] = (
+            data["Date"].dt.tz_localize(None).dt.strftime("%Y-%m-%dT%H:%M:%S")
+        )
+
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[YFinanceForexHistoricalData]:
+        """Transform the data to the standard format."""
+        return [YFinanceForexHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/futures_historical.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/futures_historical.py
new file mode 100644
index 00000000000..7233edaea53
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/futures_historical.py
@@ -0,0 +1,125 @@
+"""yfinance Futures End of Day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.futures_historical import (
+    FuturesHistoricalData,
+    FuturesHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, validator
+from yfinance import Ticker
+
+from openbb_yfinance.utils.helpers import get_futures_data
+from openbb_yfinance.utils.references import INTERVALS, MONTHS, PERIODS
+
+
+class YFinanceFuturesHistoricalQueryParams(FuturesHistoricalQueryParams):
+    """YFinance Futures End of Day Query.
+
+    Source: https://finance.yahoo.com/crypto/
+    """
+
+    interval: Optional[INTERVALS] = Field(default="1d", description="Data granularity.")
+    period: Optional[PERIODS] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("period", "")
+    )
+    prepost: bool = Field(
+        default=False, description="Include Pre and Post market data."
+    )
+    adjust: bool = Field(default=True, description="Adjust all the data automatically.")
+    back_adjust: bool = Field(
+        default=False, description="Back-adjusted data to mimic true historical prices."
+    )
+
+
+class YFinanceFuturesHistoricalData(FuturesHistoricalData):
+    """YFinance Futures End of Day Data."""
+
+    @validator("Date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return datetime object from string."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
+
+
+class YFinanceFuturesHistoricalFetcher(
+    Fetcher[
+        YFinanceFuturesHistoricalQueryParams,
+        List[YFinanceFuturesHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the yfinance endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceFuturesHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        if params.get("period") is None:
+            transformed_params = params
+
+            now = datetime.now().date()
+            if params.get("start_date") is None:
+                transformed_params["start_date"] = now - relativedelta(years=1)
+
+            if params.get("end_date") is None:
+                transformed_params["end_date"] = now
+            return YFinanceFuturesHistoricalQueryParams(**transformed_params)
+
+        return YFinanceFuturesHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceFuturesHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the yfinance endpoint."""
+        symbol = ""
+
+        if query.expiration:
+            expiry_date = datetime.strptime(query.expiration, "%Y-%m")
+            futures_data = get_futures_data()
+            exchange = futures_data[futures_data["Ticker"] == query.symbol][
+                "Exchange"
+            ].values[0]
+            symbol = f"{query.symbol}{MONTHS[expiry_date.month]}{str(expiry_date.year)[-2:]}.{exchange}"
+
+        query_symbol = symbol if symbol else f"{query.symbol}=F"
+
+        if query.period:
+            data = Ticker(query_symbol).history(
+                interval=query.interval,
+                period=query.period,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+        else:
+            data = Ticker(query_symbol).history(
+                interval=query.interval,
+                start=query.start_date,
+                end=query.end_date,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+
+        data = data.reset_index()
+        data["Date"] = (
+            data["Date"].dt.tz_localize(None).dt.strftime("%Y-%m-%dT%H:%M:%S")
+        )
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[YFinanceFuturesHistoricalData]:
+        """Transform the data to the standard format."""
+        return [YFinanceFuturesHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/income_statement.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/income_statement.py
new file mode 100644
index 00000000000..adce92c41a2
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/income_statement.py
@@ -0,0 +1,63 @@
+"""yfinance Income Statement Fetcher."""
+
+
+import json
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.income_statement import (
+    IncomeStatementData,
+    IncomeStatementQueryParams,
+)
+from pydantic import validator
+from yfinance import Ticker
+
+
+class YFinanceIncomeStatementQueryParams(IncomeStatementQueryParams):
+    """yfinance Income Statement QueryParams.
+
+    Source: https://finance.yahoo.com/
+    """
+
+
+class YFinanceIncomeStatementData(IncomeStatementData):
+    """yfinance Income Statement Data."""
+
+    # TODO: Standardize the fields
+
+    @validator("date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        return datetime.strptime(v, "%Y-%m-%d %H:%M:%S").date()
+
+
+class YFinanceIncomeStatementFetcher(
+    Fetcher[
+        YFinanceIncomeStatementQueryParams,
+        YFinanceIncomeStatementData,
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceIncomeStatementQueryParams:
+        return YFinanceIncomeStatementQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceIncomeStatementQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[YFinanceIncomeStatementData]:
+        query.period = "yearly" if query.period == "annually" else "quarterly"
+        data = Ticker(query.symbol).get_income_stmt(
+            as_dict=True, pretty=False, freq=query.period
+        )
+        data = [{"date": str(key), **value} for key, value in data.items()]
+        data = json.loads(json.dumps(data))
+
+        return [YFinanceIncomeStatementData.parse_obj(d) for d in data]
+
+    @staticmethod
+    def transform_data(
+        data: List[YFinanceIncomeStatementData],
+    ) -> List[YFinanceIncomeStatementData]:
+        return data
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/major_indices_historical.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/major_indices_historical.py
new file mode 100644
index 00000000000..00c6626c4c4
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/major_indices_historical.py
@@ -0,0 +1,116 @@
+"""yfinance Major Indices End of Day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.major_indices_historical import (
+    MajorIndicesHistoricalData,
+    MajorIndicesHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, validator
+from yfinance import Ticker
+
+from openbb_yfinance.utils.references import INTERVALS, PERIODS
+
+
+class YFinanceMajorIndicesHistoricalQueryParams(MajorIndicesHistoricalQueryParams):
+    """YFinance Major Indices End of Day Query.
+
+    Source: https://finance.yahoo.com/world-indices
+    """
+
+    interval: Optional[INTERVALS] = Field(default="1d", description="Data granularity.")
+    period: Optional[PERIODS] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("period", "")
+    )
+    prepost: bool = Field(
+        default=False, description="Include Pre and Post market data."
+    )
+    adjust: bool = Field(default=True, description="Adjust all the data automatically.")
+    back_adjust: bool = Field(
+        default=False, description="Back-adjusted data to mimic true historical prices."
+    )
+
+
+class YFinanceMajorIndicesHistoricalData(MajorIndicesHistoricalData):
+    """YFinance Major Indices End of Day Data."""
+
+    @validator("Date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return datetime object from string."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
+
+
+class YFinanceMajorIndicesHistoricalFetcher(
+    Fetcher[
+        YFinanceMajorIndicesHistoricalQueryParams,
+        List[YFinanceMajorIndicesHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the yfinance endpoints."""
+
+    @staticmethod
+    def transform_query(
+        params: Dict[str, Any]
+    ) -> YFinanceMajorIndicesHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        if params.get("period") is None:
+            transformed_params = params
+
+            now = datetime.now().date()
+            if params.get("start_date") is None:
+                transformed_params["start_date"] = now - relativedelta(years=1)
+
+            if params.get("end_date") is None:
+                transformed_params["end_date"] = now
+            return YFinanceMajorIndicesHistoricalQueryParams(**transformed_params)
+
+        return YFinanceMajorIndicesHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceMajorIndicesHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the yfinance endpoint."""
+        query.symbol = f"^{query.symbol}"
+
+        if query.period:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                period=query.period,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+        else:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                start=query.start_date,
+                end=query.end_date,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+
+        data = data.reset_index()
+        data["Date"] = (
+            data["Date"].dt.tz_localize(None).dt.strftime("%Y-%m-%dT%H:%M:%S")
+        )
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[YFinanceMajorIndicesHistoricalData]:
+        """Transform the data to the standard format."""
+        return [YFinanceMajorIndicesHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/stock_historical.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/stock_historical.py
new file mode 100644
index 00000000000..7902f6ffc8f
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/stock_historical.py
@@ -0,0 +1,112 @@
+"""yfinance Stock End of Day fetcher."""
+
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from dateutil.relativedelta import relativedelta
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_historical import (
+    StockHistoricalData,
+    StockHistoricalQueryParams,
+)
+from openbb_provider.utils.descriptions import QUERY_DESCRIPTIONS
+from pydantic import Field, validator
+from yfinance import Ticker
+
+from openbb_yfinance.utils.references import INTERVALS, PERIODS
+
+
+class YFinanceStockHistoricalQueryParams(StockHistoricalQueryParams):
+    """YFinance Stock End of Day Query.
+
+    Source: https://finance.yahoo.com/
+    """
+
+    interval: Optional[INTERVALS] = Field(default="1d", description="Data granularity.")
+    period: Optional[PERIODS] = Field(
+        default=None, description=QUERY_DESCRIPTIONS.get("period", "")
+    )
+    prepost: bool = Field(
+        default=False, description="Include Pre and Post market data."
+    )
+    adjust: bool = Field(default=True, description="Adjust all the data automatically.")
+    back_adjust: bool = Field(
+        default=False, description="Back-adjusted data to mimic true historical prices."
+    )
+
+
+class YFinanceStockHistoricalData(StockHistoricalData):
+    """YFinance Stock End of Day Data."""
+
+    @validator("Date", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        """Return datetime object from string."""
+        return datetime.strptime(v, "%Y-%m-%dT%H:%M:%S")
+
+
+class YFinanceStockHistoricalFetcher(
+    Fetcher[
+        YFinanceStockHistoricalQueryParams,
+        List[YFinanceStockHistoricalData],
+    ]
+):
+    """Transform the query, extract and transform the data from the yfinance endpoints."""
+
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceStockHistoricalQueryParams:
+        """Transform the query. Setting the start and end dates for a 1 year period."""
+        if params.get("period") is None:
+            transformed_params = params
+
+            now = datetime.now().date()
+            if params.get("start_date") is None:
+                transformed_params["start_date"] = now - relativedelta(years=1)
+
+            if params.get("end_date") is None:
+                transformed_params["end_date"] = now
+            return YFinanceStockHistoricalQueryParams(**transformed_params)
+
+        return YFinanceStockHistoricalQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceStockHistoricalQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> dict:
+        """Return the raw data from the yfinance endpoint."""
+        if query.period:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                period=query.period,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+        else:
+            data = Ticker(query.symbol).history(
+                interval=query.interval,
+                start=query.start_date,
+                end=query.end_date,
+                prepost=query.prepost,
+                auto_adjust=query.adjust,
+                back_adjust=query.back_adjust,
+                actions=False,
+                raise_errors=True,
+            )
+
+        data = data.reset_index()
+        data["Date"] = (
+            data["Date"].dt.tz_localize(None).dt.strftime("%Y-%m-%dT%H:%M:%S")
+        )
+        return data.to_dict("records")
+
+    @staticmethod
+    def transform_data(
+        data: dict,
+    ) -> List[YFinanceStockHistoricalData]:
+        """Transform the data to the standard format."""
+        return [YFinanceStockHistoricalData.parse_obj(d) for d in data]
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/models/stock_news.py b/openbb_sdk/providers/yfinance/openbb_yfinance/models/stock_news.py
new file mode 100644
index 00000000000..ad587b32da4
--- /dev/null
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/models/stock_news.py
@@ -0,0 +1,72 @@
+"""yfinance Stock News fetcher."""
+
+
+import json
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from openbb_provider.abstract.fetcher import Fetcher
+from openbb_provider.standard_models.stock_news import (
+    StockNewsData,
+    StockNewsQueryParams,
+)
+from pydantic import Field, validator
+from yfinance import Ticker
+
+
+class YFinanceStockNewsQueryParams(StockNewsQueryParams):
+    """YFinance Stock News Query.
+
+    Source: https://finance.yahoo.com/news/
+    """
+
+
+class YFinanceStockNewsData(StockNewsData):
+    """YFinance Stock News Data."""
+
+    class Config:
+        fields = {
+            "date": "providerPublishTime",
+            "url": "link",
+        }
+
+    uuid: str = Field(description="Unique identifier for the news article")
+    publisher: str = Field(description="Publisher of the news article")
+    type: str = Field(description="Type of the news article")
+    thumbnail: Dict[str, Any] = Field(
+        description="Thumbnail related data to the ticker news article."
+    )
+    relatedTickers: str = Field(description="Tickers related to the news article.")
+
+    @validator("providerPublishTime", pre=True, check_fields=False)
+    def date_validate(cls, v):  # pylint: disable=E0213
+        return datetime.fromtimestamp(v)
+
+
+class YFinanceStockNewsFetcher(
+    Fetcher[
+        YFinanceStockNewsQueryParams,
+        YFinanceStockNewsData,
+    ]
+):
+    @staticmethod
+    def transform_query(params: Dict[str, Any]) -> YFinanceStockNewsQueryParams:
+        return YFinanceStockNewsQueryParams(**params)
+
+    @staticmethod
+    def extract_data(
+        query: YFinanceStockNewsQueryParams,
+        credentials: Optional[Dict[str, str]],
+        **kwargs: Any,
+    ) -> List[YFinanceStockNewsData]:
+        data = Ticker(query.symbols).get_news()
+        data = json.loads(json.dumps(data))
+        data = [{**d, "relatedTickers": ",".join(d["relatedTickers"])} for d in data]
+
+        return [YFinanceStockNewsData.parse_obj(d) for d in data]
+
+    @staticmethod
+    def transform_data(
+        data: List[YFinanceStockNewsData],
+    ) -> List[YFinanceStockNewsData]:
+        return data
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/utils/helpers.py b/openbb_sdk/providers/yfinance/openbb_yfinance/utils/helpers.py
index a77751a185a..089cb081e7c 100644
--- a/openbb_sdk/providers/yfinance/openbb_yfinance/utils/helpers.py
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/utils/helpers.py
@@ -6,7 +6,7 @@ from datetime import (
     datetime,
 )
 from pathlib import Path
-from typing import Optional
+from typing import Any, Literal, Optional, Union
 
 import pandas as pd
 import yfinance as yf
@@ -77,3 +77,98 @@ def get_futures_curve(symbol: str, date: Optional[dateType]) -> pd.DataFrame:
             {"Last Price": historical_curve, "expiration": futures_index}
         )
     return pd.DataFrame({"Last Price": futures_curve, "expiration": futures_index})
+
+
+def yf_download(
+    symbol: str,
+    start_date: Optional[Union[str, dateType]] = None,
+    end_date: Optional[Union[str, dateType]] = None,
+    interval: str = "1d",
+    period: str = "max",
+    prepost: bool = False,
+    actions: bool = False,
+    auto_adjust: bool = False,
+    back_adjust: bool = False,
+    progress: bool = False,
+    ignore_tz: bool = True,
+    keepna: bool = False,
+    repair: bool = False,
+    rounding: bool = False,
+    group_by: Literal["symbol", "column"] = "column",
+    **kwargs: Any,
+) -> pd.DataFrame:
+    """Base level yFinance OHLC helper function for returning any ticker and interval available."""
+
+    symbol = symbol.upper()
+    _start_date = start_date
+
+    if interval in ["60m", "1h"]:
+        period = "2y" if period in ["5y", "10y", "max"] else period
+        _start_date = None
+
+    if interval in ["2m", "5m", "15m", "30m", "90m"]:
+        _start_date = (datetime.now().date() - relativedelta(days=59)).strftime(
+            "%Y-%m-%d"
+        )
+
+    if interval == "1m":
+        period = "5d"
+        _start_date = None
+
+    data = yf.download(
+        tickers=symbol,
+        start=_start_date,
+        end=None,
+        interval=interval,
+        period=period,
+        prepost=prepost,
+        auto_adjust=auto_adjust,
+        back_adjust=back_adjust,
+        actions=actions,
+        progress=progress,
+        ignore_tz=ignore_tz,
+        keepna=keepna,
+        repair=repair,
+        rounding=rounding,
+        group_by=group_by,
+    )
+    if not data.empty:
+        data = data.reset_index()
+        data = data.rename(columns={"Date": "date", "Datetime": "date"})
+        data["date"] = pd.to_datetime(data["date"])
+        data = data[data["Open"] > 0]
+
+        if start_date is not None:
+            data = data[data["date"] >= pd.to_datetime(start_date)]
+            if end_date is not None and pd.to_datetime(end_date) > pd.to_datetime(
+                start_date
+            ):
+                data = data[
+                    data["date"] <= (pd.to_datetime(end_date) + relativedelta(days=1))
+                ]
+
+        if period not in [
+            "max",
+            "1d",
+            "5d",
+            "1wk",
+            "1mo",
+            "3mo",
+            "6mo",
+            "1y",
+            "2y",
+            "5y",
+            "10y",
+        ]:
+            data["date"] = (
+                data["date"].dt.tz_localize(None).dt.strftime("%Y-%m-%d %H:%M:%S")
+            )
+        if interval not in ["1m", "2m", "5m", "15m", "30m", "90m", "60m", "1h"]:
+            data["date"] = data["date"].dt.tz_localize(None).dt.strftime("%Y-%m-%d")
+
+        if actions is False:
+            data = data.drop(columns=["Adj Close"])
+
+        data.columns = data.columns.str.lower().to_list()
+
+    return data
diff --git a/openbb_sdk/providers/yfinance/openbb_yfinance/utils/references.py b/openbb_sdk/providers/yfinance/openbb_yfinance/utils/references.py
index d6139a338e3..5c75a1f29c9 100644
--- a/openbb_sdk/providers/yfinance/openbb_yfinance/utils/references.py
+++ b/openbb_sdk/providers/yfinance/openbb_yfinance/utils/references.py
@@ -24,3 +24,589 @@ MONTHS = {
     11: "X",
     12: "Z",
 }
+
+INDICES = {
+    "sp500": {"name": "S&P 500 Index", "ticker": "^GSPC"},
+    "spx": {"name": "S&P 500 Index", "ticker": "^SPX"},
+    "sp400": {"name": "S&P 400 Mid Cap Index", "ticker": "^SP400"},
+    "sp600": {"name": "S&P 600 Small Cap Index", "ticker": "^SP600"},
+    "sp500tr": {"name": "S&P 500 TR Index", "ticker": "^SP500TR"},
+    "sp_xsp": {"name": "S&P 500 Mini SPX Options Index", "ticker": "^XSP"},
+    "nyse_ny": {"name": "NYSE US 100 Index", "ticker": "^NY"},
+    "dow_djus": {"name": "Dow Jones US Index", "ticker": "^DJUS"},
+    "nyse": {"name": "NYSE Composite Index", "ticker": "^NYA"},
+    "amex": {"name": "NYSE-AMEX Composite Index", "ticker": "^XAX"},
+    "nasdaq": {"name": "Nasdaq Composite Index", "ticker": "^IXIC"},
+    "nasdaq100": {"name": "NASDAQ 100", "ticker": "^NDX"},
+    "nasdaq100_ew": {"name": "NASDAQ 100 Equal Weighted Index", "ticker": "^NDXE"},
+    "nasdaq50": {"name": "NASDAQ Q50 Index", "ticker": "^NXTQ"},
+    "russell1000": {"name": "Russell 1000 Index", "ticker": "^RUI"},
+    "russell2000": {"name": "Russell 2000 Index", "ticker": "^RUT"},
+    "cboe_bxr": {"name": "CBOE Russell 2000 Buy-Write Index", "ticker": "^BXR"},
+    "cboe_bxrt": {
+        "name": "CBOE Russell 2000 30-Delta Buy-Write Index",
+        "ticker": "^BXRT",
+    },
+    "russell3000": {"name": "Russell 3000 Index", "ticker": "^RUA"},
+    "russellvalue": {"name": "Russell 2000 Value Index", "ticker": "^RUJ"},
+    "russellgrowth": {"name": "Russell 2000 Growth Index", "ticker": "^RUO"},
+    "w5000": {"name": "Wilshire 5000", "ticker": "^W5000"},
+    "w5000flt": {"name": "Wilshire 5000 Float Adjusted Index", "ticker": "^W5000FLT"},
+    "dow_dja": {"name": "Dow Jones Composite Average Index", "ticker": "^DJA"},
+    "dow_dji": {"name": "Dow Jones Industrial Average Index", "ticker": "^DJI"},
+    "ca_tsx": {"name": "TSX Composite Index (CAD)", "ticker": "^GSPTSE"},
+    "ca_banks": {"name": "S&P/TSX Composite Banks Index (CAD)", "ticker": "TXBA.TS"},
+    "mx_ipc": {"name": "IPC Mexico Index (MXN)", "ticker": "^MXX"},
+    "arca_mxy": {"name": "NYSE ARCA Mexico Index (USD)", "ticker": "^MXY"},
+    "br_bvsp": {"name": "IBOVESPA Sao Paulo Brazil Index (BRL)", "ticker": "^BVSP"},
+    "br_ivbx": {"name": "IVBX2 Indice Valour (BRL)", "ticker": "^IVBX"},
+    "ar_mervel": {"name": "S&P MERVAL TR Index (USD)", "ticker": "M.BA"},
+    "eu_fteu1": {"name": "FTSE Eurotop 100 Index (EUR)", "ticker": "^FTEU1"},
+    "eu_speup": {"name": "S&P Europe 350 Index (EUR)", "ticker": "^SPEUP"},
+    "eu_n100": {"name": "Euronext 100 Index (EUR)", "ticker": "^N100"},
+    "ftse100": {"name": "FTSE Global 100 Index (GBP)", "ticker": "^FTSE"},
+    "ftse250": {"name": "FTSE Global 250 Index (GBP)", "ticker": "^FTMC"},
+    "ftse350": {"name": "FTSE Global 350 Index (GBP)", "ticker": "^FTLC"},
+    "ftai": {"name": "FTSE AIM All-Share Global Index (GBP)", "ticker": "^FTAI"},
+    "uk_ftas": {"name": "UK FTSE All-Share Index (GBP)", "ticker": "^FTAS"},
+    "uk_spuk": {"name": "S&P United Kingdom Index (PDS)", "ticker": "^SPUK"},
+    "uk_100": {"name": "CBOE UK 100 Index (GBP)", "ticker": "^BUK100P"},
+    "ie_iseq": {"name": "ISEQ Irish All Shares Index (EUR)", "ticker": "^ISEQ"},
+    "nl_aex": {"name": "Euronext Dutch 25 Index (EUR)", "ticker": "^AEX"},
+    "nl_amx": {"name": "Euronext Dutch Mid Cap Index (EUR)", "ticker": "^AMX"},
+    "at_atx": {"name": "Wiener Börse Austrian 20 Index (EUR)", "ticker": "^ATX"},
+    "at_atx5": {"name": "Vienna ATX Five Index (EUR)", "ticker": "^ATX5"},
+    "at_prime": {"name": "Vienna ATX Prime Index (EUR)", "ticker": "^ATXPRIME"},
+    "ch_stoxx": {"name": "Zurich STXE 600 PR Index (EUR)", "ticker": "^STOXX"},
+    "ch_stoxx50e": {"name": "Zurich ESTX 50 PR Index (EUR)", "ticker": "^STOXX50E"},
+    "se_omx30": {"name": "OMX Stockholm 30 Index (SEK)", "ticker": "^OMX"},
+    "se_omxspi": {"name": "OMX Stockholm All Share PI (SEK)", "ticker": "^OMXSPI"},
+    "se_benchmark": {"name": "OMX Stockholm Benchmark GI (SEK)", "ticker": "^OMXSBGI"},
+    "dk_benchmark": {"name": "OMX Copenhagen Benchmark GI (DKK)", "ticker": "^OMXCBGI"},
+    "dk_omxc25": {"name": "OMX Copenhagen 25 Index (DKK)", "ticker": "^OMXC25"},
+    "fi_omxh25": {"name": "OMX Helsinki 25 (EUR)", "ticker": "^OMXH25"},
+    "de_dax40": {"name": "DAX Performance Index (EUR)", "ticker": "^GDAXI"},
+    "de_mdax60": {"name": "DAX Mid Cap Performance Index (EUR)", "ticker": "^MDAXI"},
+    "de_sdax70": {"name": "DAX Small Cap Performance Index (EUR)", "ticker": "^SDAXI"},
+    "de_tecdax30": {"name": "DAX Tech Sector TR Index (EUR)", "ticker": "^TECDAX"},
+    "fr_cac40": {"name": "CAC 40 PR Index (EUR)", "ticker": "^FCHI"},
+    "fr_next20": {"name": "CAC Next 20 Index (EUR)", "ticker": "^CN20"},
+    "it_mib40": {"name": "FTSE MIB 40 Index (EUR)", "ticker": "FTSEMIB.MI"},
+    "be_bel20": {"name": "BEL 20 Brussels Index (EUR)", "ticker": "^BFX"},
+    "pt_bvlg": {
+        "name": "Lisbon PSI All-Share Index GR (EUR)",
+        "ticker": "^BVLG",
+    },
+    "es_ibex35": {"name": "IBEX 35 - Madrid CATS (EUR)", "ticker": "^IBEX"},
+    "in_bse": {"name": "S&P Bombay SENSEX (INR)", "ticker": "^BSESN"},
+    "in_bse500": {
+        "name": "S&P BSE 500 Index (INR)",
+        "ticker": "BSE-500.BO",
+    },
+    "in_bse200": {
+        "name": "S&P BSE 200 Index (INR)",
+        "ticker": "BSE-200.BO",
+    },
+    "in_bse100": {
+        "name": "S&P BSE 100 Index (INR)",
+        "ticker": "BSE-100.BO",
+    },
+    "in_bse_mcap": {
+        "name": "S&P Bombay Mid Cap Index (INR)",
+        "ticker": "BSE-MIDCAP.BO",
+    },
+    "in_bse_scap": {
+        "name": "S&P Bombay Small Cap Index (INR)",
+        "ticker": "BSE-SMLCAP.BO",
+    },
+    "in_nse50": {"name": "NSE Nifty 50 Index (INR)", "ticker": "^NSEI"},
+    "in_nse_mcap": {"name": "NSE Nifty 50 Mid Cap Index (INR)", "ticker": "^NSEMDCP50"},
+    "in_nse_bank": {
+        "name": "NSE Nifty Bank Industry Index (INR)",
+        "ticker": "^NSEBANK",
+    },
+    "in_nse500": {"name": "NSE Nifty 500 Index (INR)", "ticker": "^CRSLDX"},
+    "il_ta125": {"name": "Tel-Aviv 125 Index (ILS)", "ticker": "^TA125.TA"},
+    "za_shariah": {
+        "name": "Johannesburg Shariah All Share Index (ZAR)",
+        "ticker": "^J143.JO",
+    },
+    "za_jo": {"name": "Johannesburg All Share Index (ZAR)", "ticker": "^J203.JO"},
+    "za_jo_mcap": {
+        "name": "Johannesburg Large and Mid Cap Index (ZAR)",
+        "ticker": "^J206.JO",
+    },
+    "za_jo_altex": {
+        "name": "Johannesburg Alt Exchange Index (ZAR)",
+        "ticker": "^J232.JO",
+    },
+    "ru_moex": {"name": "MOEX Russia Index (RUB)", "ticker": "IMOEX.ME"},
+    "au_aord": {"name": "Australia All Ordinary Share Index (AUD)", "ticker": "^AORD"},
+    "au_small": {"name": "S&P/ASX Small Ordinaries Index (AUD)", "ticker": "^AXSO"},
+    "au_asx20": {
+        "name": "S&P/ASX 20 Index (AUD)",
+        "ticker": "^ATLI",
+    },
+    "au_asx50": {
+        "name": "S&P/ASX 50 Index (AUD)",
+        "ticker": "^AFLI",
+    },
+    "au_asx50_mid": {
+        "name": "S&P/ASX Mid Cap 50 Index (AUD)",
+        "ticker": "^AXMD",
+    },
+    "au_asx100": {
+        "name": "S&P/ASX 100 Index (AUD)",
+        "ticker": "^ATOI",
+    },
+    "au_asx200": {"name": "S&P/ASX 200 Index (AUD)", "ticker": "^AXJO"},
+    "au_asx300": {
+        "name": "S&P/ASX 300 Index (AUD)",
+        "ticker": "^AXKO",
+    },
+    "au_energy": {
+        "name": "S&P/ASX 200 Energy Sector Index (AUD)",
+        "ticker": "^AXEJ",
+    },
+    "au_resources": {
+        "name": "S&P/ASX 200 Resources Sector Index (AUD)",
+        "ticker": "^AXJR",
+    },
+    "au_materials": {
+        "name": "S&P/ASX 200 Materials Sector Index (AUD)",
+        "ticker": "^AXMJ",
+    },
+    "au_mining": {
+        "name": "S&P/ASX 300 Metals and Mining Sector Index (AUD)",
+        "ticker": "^AXMM",
+    },
+    "au_industrials": {
+        "name": "S&P/ASX 200 Industrials Sector Index (AUD)",
+        "ticker": "^AXNJ",
+    },
+    "au_discretionary": {
+        "name": "S&P/ASX 200 Consumer Discretionary Sector Index (AUD)",
+        "ticker": "^AXDJ",
+    },
+    "au_staples": {
+        "name": "S&P/ASX 200 Consumer Staples Sector Index (AUD)",
+        "ticker": "^AXSJ",
+    },
+    "au_health": {
+        "name": "S&P/ASX 200 Health Care Sector Index (AUD)",
+        "ticker": "^AXHJ",
+    },
+    "au_financials": {
+        "name": "S&P/ASX 200 Financials Sector Index (AUD)",
+        "ticker": "^AXFJ",
+    },
+    "au_reit": {"name": "S&P/ASX 200 A-REIT Industry Index (AUD)", "ticker": "^AXPJ"},
+    "au_tech": {"name": "S&P/ASX 200 Info Tech Sector Index (AUD)", "ticker": "^AXIJ"},
+    "au_communications": {
+        "name": "S&P/ASX 200 Communications Sector Index (AUD)",
+        "ticker": "^AXTJ",
+    },
+    "au_utilities": {
+        "name": "S&P/ASX 200 Utilities Sector Index (AUD)",
+        "ticker": "^AXUJ",
+    },
+    "nz50": {"name": "S&P New Zealand 50 Index (NZD)", "ticker": "^nz50"},
+    "nz_small": {"name": "S&P/NZX Small Cap Index (NZD)", "ticker": "^NZSC"},
+    "kr_kospi": {"name": "KOSPI Composite Index (KRW)", "ticker": "^KS11"},
+    "jp_arca": {"name": "NYSE ARCA Japan Index (JPY)", "ticker": "^JPN"},
+    "jp_n225": {"name": "Nikkei 255 Index (JPY)", "ticker": "^N225"},
+    "jp_n300": {"name": "Nikkei 300 Index (JPY)", "ticker": "^N300"},
+    "jp_nknr": {"name": "Nikkei Avg Net TR Index (JPY)", "ticker": "^NKVI.OS"},
+    "jp_nkrc": {"name": "Nikkei Avg Risk Control Index (JPY)", "ticker": "^NKRC.OS"},
+    "jp_nklv": {"name": "Nikkei Avg Leverage Index (JPY)", "ticker": "^NKLV.OS"},
+    "jp_nkcc": {"name": "Nikkei Avg Covered Call Index (JPY)", "ticker": "^NKCC.OS"},
+    "jp_nkhd": {
+        "name": "Nikkei Avg High Dividend Yield Index (JPY)",
+        "ticker": "^NKHD.OS",
+    },
+    "jp_auto": {
+        "name": "Nikkei 500 Auto & Auto Parts Index (JPY)",
+        "ticker": "^NG17.OS",
+    },
+    "jp_fintech": {
+        "name": "Global Fintech Japan Hedged Index (JPY)",
+        "ticker": "^FDSFTPRJPY",
+    },
+    "jp_nkdh": {"name": "Nikkei Average USD Hedge Index (JPY)", "ticker": "^NKDH.OS"},
+    "jp_nkeh": {"name": "Nikkei Average EUR Hedge Index (JPY)", "ticker": "^NKEH.OS"},
+    "jp_ndiv": {
+        "name": "Nikkei Average Double Inverse Index (JPY)",
+        "ticker": "^NDIV.OS",
+    },
+    "cn_csi300": {"name": "China CSI 300 Index (CNY)", "ticker": "000300.SS"},
+    "cn_sse_comp": {"name": "SSE Composite Index (CNY)", "ticker": "000001.SS"},
+    "cn_sse_a": {"name": "SSE A Share Index (CNY)", "ticker": "000002.SS"},
+    "cn_szse_comp": {"name": "SZSE Component Index (CNY)", "ticker": "399001.SZ"},
+    "cn_szse_a": {"name": "SZSE A-Shares Index (CNY)", "ticker": "399107.SZ"},
+    "tw_twii": {"name": "TSEC Weighted Index (TWD)", "ticker": "^TWII"},
+    "tw_tcii": {"name": "TSEC Cement and Ceramics Subindex (TWD)", "ticker": "^TCII"},
+    "tw_tfii": {"name": "TSEC Foods Subindex (TWD)", "ticker": "^TFII"},
+    "tw_tfni": {"name": "TSEC Finance Subindex (TWD)", "ticker": "^TFNI"},
+    "tw_tpai": {"name": "TSEC Paper and Pulp Subindex (TWD)", "ticker": "^TPAI"},
+    "hk_hsi": {"name": "Hang Seng Index (HKD)", "ticker": "^HSI"},
+    "hk_utilities": {
+        "name": "Hang Seng Utilities Sector Index (HKD)",
+        "ticker": "^HSNU",
+    },
+    "hk_china": {
+        "name": "Hang Seng China-Affiliated Corporations Index (HKD)",
+        "ticker": "^HSCC",
+    },
+    "hk_finance": {"name": "Hang Seng Finance Sector Index (HKD)", "ticker": "^HSNF"},
+    "hk_properties": {
+        "name": "Hang Seng Properties Sector Index (HKD)",
+        "ticker": "^HSNP",
+    },
+    "hk_hko": {"name": "NYSE ARCA Hong Kong Options Index (USD)", "ticker": "^HKO"},
+    "hk_titans30": {
+        "name": "Dow Jones Hong Kong Titans 30 Index (HKD)",
+        "ticker": "^XLHK",
+    },
+    "id_jkse": {"name": "Jakarta Composite Index (IDR)", "ticker": "^JKSE"},
+    "id_lq45": {
+        "name": "Indonesia Stock Exchange LQ45 Index (IDR)",
+        "ticker": "^JKLQ45",
+    },
+    "my_klci": {"name": "FTSE Kuala Lumpur Composite Index (MYR)", "ticker": "^KLSE"},
+    "ph_psei": {"name": "Philippine Stock Exchange Index (PHP)", "ticker": "PSEI.PS"},
+    "sg_sti": {"name": "STI Singapore Index (SGD)", "ticker": "^STI"},
+    "th_set": {"name": "Thailand SET Index (THB)", "ticker": "^SET.BK"},
+    "sp_energy_ig": {
+        "name": "S&P 500 Energy (Industry Group) Index",
+        "ticker": "^SP500-1010",
+    },
+    "sp_energy_equipment": {
+        "name": "S&P 500 Energy Equipment & Services Industry Index",
+        "ticker": "^SP500-101010",
+    },
+    "sp_energy_oil": {
+        "name": "S&P 500 Oil, Gas & Consumable Fuels Industry Index",
+        "ticker": "^SP500-101020",
+    },
+    "sp_materials_sector": {
+        "name": "S&P 500 Materials Sector Index",
+        "ticker": "^SP500-15",
+    },
+    "sp_materials_ig": {
+        "name": "S&P 500 Materials (Industry Group) Index",
+        "ticker": "^SP500-1510",
+    },
+    "sp_materials_construction": {
+        "name": "S&P 500 Construction Materials Industry Index",
+        "ticker": "^SP500-151020",
+    },
+    "sp_materials_metals": {
+        "name": "S&P 500 Mining & Metals Industry Index",
+        "ticker": "^SP500-151040",
+    },
+    "sp_industrials_sector": {
+        "name": "S&P 500 Industrials Sector Index",
+        "ticker": "^SP500-20",
+    },
+    "sp_industrials_goods_ig": {
+        "name": "S&P 500 Capital Goods (Industry Group) Index",
+        "ticker": "^SP500-2010",
+    },
+    "sp_industrials_aerospace": {
+        "name": "S&P 500 Aerospace & Defense Industry Index",
+        "ticker": "^SP500-201010",
+    },
+    "sp_industrials_building": {
+        "name": "S&P 500 Building Products Industry Index",
+        "ticker": "^SP500-201020",
+    },
+    "sp_industrials_construction": {
+        "name": "S&P 500 Construction & Engineering Industry Index",
+        "ticker": "^SP500-201030",
+    },
+    "sp_industrials_electrical": {
+        "name": "S&P 500 Electrical Equipment Industry Index",
+        "ticker": "^SP500-201040",
+    },
+    "sp_industrials_conglomerates": {
+        "name": "S&P 500 Industrial Conglomerates Industry Index",
+        "ticker": "^SP500-201050",
+    },
+    "sp_industrials_machinery": {
+        "name": "S&P 500 Machinery Industry Index",
+        "ticker": "^SP500-201060",
+    },
+    "sp_industrials_distributors": {
+        "name": "S&P 500 Trading Companies & Distributors Industry Index",
+        "ticker": "^SP500-201070",
+    },
+    "sp_industrials_services_ig": {
+        "name": "S&P 500 Commercial & Professional Services (Industry Group) Index",
+        "ticker": "^SP500-2020",
+    },
+    "sp_industrials_services_supplies": {
+        "name": "S&P 500 Commercial Services & Supplies Industry Index",
+        "ticker": "^SP500-202010",
+    },
+    "sp_industrials_transport_ig": {
+        "name": "S&P 500 Transportation (Industry Group) Index",
+        "ticker": "^SP500-2030",
+    },
+    "sp_industrials_transport_air": {
+        "name": "S&P 500 Air Freight & Logistics Industry",
+        "ticker": "^SP500-203010",
+    },
+    "sp_industrials_transport_airlines": {
+        "name": "S&P 500 Airlines Industry Index",
+        "ticker": "^SP500-203020",
+    },
+    "sp_industrials_transport_ground": {
+        "name": "S&P 500 Road & Rail Industry Index",
+        "ticker": "^SP500-203040",
+    },
+    "sp_discretionary_sector": {
+        "name": "S&P 500 Consumer Discretionary Index",
+        "ticker": "^SP500-25",
+    },
+    "sp_discretionary_autos-ig": {
+        "name": "S&P 500 Automobiles and Components (Industry Group) Index",
+        "ticker": "^SP500-2510",
+    },
+    "sp_discretionary_auto_components": {
+        "name": "S&P 500 Auto Components Industry Index",
+        "ticker": "^SP500-251010",
+    },
+    "sp_discretionary_autos": {
+        "name": "S&P 500 Automobiles Industry Index",
+        "ticker": "^SP500-251020",
+    },
+    "sp_discretionary_durables_ig": {
+        "name": "S&P 500 Consumer Durables & Apparel (Industry Group) Index",
+        "ticker": "^SP500-2520",
+    },
+    "sp_discretionary_durables_household": {
+        "name": "S&P 500 Household Durables Industry Index",
+        "ticker": "^SP500-252010",
+    },
+    "sp_discretionary_leisure": {
+        "name": "S&P 500 Leisure Products Industry Index",
+        "ticker": "^SP500-252020",
+    },
+    "sp_discretionary_textiles": {
+        "name": "S&P 500 Textiles, Apparel & Luxury Goods Industry Index",
+        "ticker": "^SP500-252030",
+    },
+    "sp_discretionary_services_consumer": {
+        "name": "S&P 500 Consumer Services (Industry Group) Index",
+        "ticker": "^SP500-2530",
+    },
+    "sp_staples_sector": {
+        "name": "S&P 500 Consumer Staples Sector Index",
+        "ticker": "^SP500-30",
+    },
+    "sp_staples_retail_ig": {
+        "name": "S&P 500 Food & Staples Retailing (Industry Group) Index",
+        "ticker": "^SP500-3010",
+    },
+    "sp_staples_food_ig": {
+        "name": "S&P 500 Food Beverage & Tobacco (Industry Group) Index",
+        "ticker": "^SP500-3020",
+    },
+    "sp_staples_beverages": {
+        "name": "S&P 500 Beverages Industry Index",
+        "ticker": "^SP500-302010",
+    },
+    "sp_staples_products_food": {
+        "name": "S&P 500 Food Products Industry Index",
+        "ticker": "^SP500-302020",
+    },
+    "sp_staples_tobacco": {
+        "name": "S&P 500 Tobacco Industry Index",
+        "ticker": "^SP500-302030",
+    },
+    "sp_staples_household_ig": {
+        "name": "S&P 500 Household & Personal Products (Industry Group) Index",
+        "ticker": "^SP500-3030",
+    },
+    "sp_staples_products_household": {
+        "name": "S&P 500 Household Products Industry Index",
+        "ticker": "^SP500-303010",
+    },
+    "sp_staples_products_personal": {
+        "name": "S&P 500 Personal Products Industry Index",
+        "ticker": "^SP500-303020",
+    },
+    "sp_health_sector": {
+        "name": "S&P 500 Health Care Sector Index",
+        "ticker": "^SP500-35",
+    },
+    "sp_health_equipment": {
+        "name": "S&P 500 Health Care Equipment & Services (Industry Group) Index",
+        "ticker": "^SP500-3510",
+    },
+    "sp_health_supplies": {
+        "name": "S&P 500 Health Care Equipment & Supplies Industry Index",
+        "ticker": "^SP500-351010",
+    },
+    "sp_health_providers": {
+        "name": "S&P 500 Health Care Providers & Services Industry Index",
+        "ticker": "^SP500-351020",
+    },
+    "sp_health_sciences": {
+        "name": "S&P 500 Pharmaceuticals, Biotechnology & Life Sciences (Industry Group) Index",
+        "ticker": "^SP500-3520",
+    },
+    "sp_health_biotech": {
+        "name": "S&P 500 Biotechnology Industry Index",
+        "ticker": "^SP500-352010",
+    },
+    "sp_health_pharma": {
+        "name": "S&P 500 Pharmaceuticals Industry Index",
+        "ticker": "^SP500-352020",
+    },
+    "sp_financials_sector": {
+        "name": "S&P 500 Financials Sector Index",
+        "ticker": "^SP500-40",
+    },
+    "sp_financials_diversified_ig": {
+        "name": "S&P 500 Diversified Financials (Industry Group) Index",
+        "ticker": "^SP500-4020",
+    },
+    "sp_financials_services": {
+        "name": "S&P 500 Diversified Financial Services Industry Index",
+        "ticker": "^SP500-402010",
+    },
+    "sp_financials_consumer": {
+        "name": "S&P 500 Consumer Finance Industry Index",
+        "ticker": "^SP500-402020",
+    },
+    "sp_financials_capital": {
+        "name": "S&P 500 Capital Markets Industry Index",
+        "ticker": "^SP500-402030",
+    },
+    "sp_it_sector": {
+        "name": "S&P 500 IT Sector Index",
+        "ticker": "^SP500-45",
+    },
+    "sp_it_saas_ig": {
+        "name": "S&P 500 Software and Services (Industry Group) Index",
+        "ticker": "^SP500-4510",
+    },
+    "sp_it_software": {
+        "name": "S&P 500 Software Industry Index",
+        "ticker": "^SP500-451030",
+    },
+    "sp_it_hardware": {
+        "name": "S&P 500 Technology Hardware Equipment (Industry Group) Index",
+        "ticker": "^SP500-4520",
+    },
+    "sp_it_semi": {
+        "name": "S&P 500 Semiconductor & Semiconductor Equipment Industry",
+        "ticker": "^SP500-453010",
+    },
+    "sp_communications_sector": {
+        "name": "S&P 500 Communications Sector Index",
+        "ticker": "^SP500-50",
+    },
+    "sp_communications_telecom": {
+        "name": "S&P 500 Diversified Telecommunications Services Industry Index",
+        "ticker": "^SP500-501010",
+    },
+    "sp_utilities_sector": {
+        "name": "S&P 500 Utilities Sector Index",
+        "ticker": "^SP500-55",
+    },
+    "sp_utilities_electricity": {
+        "name": "S&P 500 Electric Utilities Index",
+        "ticker": "^SP500-551010",
+    },
+    "sp_utilities_multis": {
+        "name": "S&P 500 Multi-Utilities Industry Index",
+        "ticker": "^SP500-551030",
+    },
+    "sp_re_sector": {
+        "name": "S&P 500 Real Estate Sector Index",
+        "ticker": "^SP500-60",
+    },
+    "sp_re_ig": {
+        "name": "S&P 500 Real Estate (Industry Group) Index",
+        "ticker": "^SP500-6010",
+    },
+    "sphyda": {"name": "S&P High Yield Aristocrats Index", "ticker": "^SPHYDA"},
+    "dow_djt": {"name": "Dow Jones Transportation Average Index", "ticker": "^DJT"},
+    "dow_dju": {"name": "Dow Jones Utility Average Index", "ticker": "^DJU"},
+    "dow_rci": {"name": "Dow Jones Composite All REIT Index", "ticker": "^RCI"},
+    "reit_fnar": {"name": "FTSE Nareit All Equity REITs Index", "ticker": "^FNAR"},
+    "nq_ixch": {"name": "NASDAQ Health Care Index", "ticker": "^IXCH"},
+    "nq_nbi": {"name": "NASDAQ Biotech Index", "ticker": "^NBI"},
+    "nq_tech": {"name": "NASDAQ 100 Technology Sector Index", "ticker": "^NDXT"},
+    "nq_ex_tech": {"name": "NASDAQ 100 Ex-Tech Sector Index", "ticker": "^NDXX"},
+    "nq_ixtc": {"name": "NASDAQ Telecommunications Index", "ticker": "^IXTC"},
+    "nq_inds": {"name": "NASDAQ Industrial Index", "ticker": "^INDS"},
+    "nq_ixco": {"name": "NASDAQ Computer Index", "ticker": "^INCO"},
+    "nq_bank": {"name": "NASDAQ Bank Index", "ticker": "^BANK"},
+    "nq_bkx": {"name": "KBW NASDAQ Bank Index", "ticker": "^BKX"},
+    "nq_krx": {"name": "KBW NASDAQ Regional Bank Index", "ticker": "^KRX"},
+    "nq_kix": {"name": "KBW NASDAQ Insurance Index", "ticker": "^KIX"},
+    "nq_ksx": {"name": "KBW NASDAQ Capital Markets Index", "ticker": "^KSX"},
+    "nq_tran": {"name": "NASDAQ Transportation Index", "ticker": "^TRAN"},
+    "ice_auto": {"name": "ICE FactSet Global NextGen Auto Index", "ticker": "^ICEFSNA"},
+    "ice_comm": {
+        "name": "ICE FactSet Global NextGen Communications Index",
+        "ticker": "^ICEFSNC",
+    },
+    "nyse_nyl": {"name": "NYSE World Leaders Index", "ticker": "^NYL"},
+    "nyse_nyi": {"name": "NYSE International 100 Index", "ticker": "^NYI"},
+    "nyse_nyy": {"name": "NYSE TMT Index", "ticker": "^NYY"},
+    "nyse_fang": {"name": "NYSE FANG+TM index", "ticker": "^NYFANG"},
+    "arca_xmi": {"name": "NYSE ARCA Major Market Index", "ticker": "^XMI"},
+    "arca_xbd": {"name": "NYSE ARCA Securities Broker/Dealer Index", "ticker": "^XBD"},
+    "arca_xii": {"name": "NYSE ARCA Institutional Index", "ticker": "^XII"},
+    "arca_xoi": {"name": "NYSE ARCA Oil and Gas Index", "ticker": "^XOI"},
+    "arca_xng": {"name": "NYSE ARCA Natural Gas Index", "ticker": "^XNG"},
+    "arca_hui": {"name": "NYSE ARCA Gold Bugs Index", "ticker": "^HUI"},
+    "arca_ixb": {"name": "NYSE Materials Select Sector Index", "ticker": "^IXB"},
+    "arca_drg": {"name": "NYSE ARCA Phramaceutical Index", "ticker": "^DRG"},
+    "arca_btk": {"name": "NYSE ARCA Biotech Index", "ticker": "^BKT"},
+    "arca_pse": {"name": "NYSE ARCA Tech 100 Index", "ticker": "^PSE"},
+    "arca_nwx": {"name": "NYSE ARCA Networking Index", "ticker": "^NWX"},
+    "arca_xci": {"name": "NYSE ARCA Computer Tech Index", "ticker": "^XCI"},
+    "arca_xal": {"name": "NYSE ARCA Airline Index", "ticker": "^XAL"},
+    "arca_xtc": {"name": "NYSE ARCA N.A. Telecom Industry Index", "ticker": "^XTC"},
+    "phlx_sox": {"name": "PHLX Semiconductor Index", "ticker": "^SOX"},
+    "phlx_xau": {"name": "PHLX Gold/Silver Index", "ticker": "^XAU"},
+    "phlx_hgx": {"name": "PHLX Housing Sector Index", "ticker": "^HGX"},
+    "phlx_osx": {"name": "PHLX Oil Services Sector Index", "ticker": "^OSX"},
+    "phlx_uty": {"name": "PHLX Utility Sector Index", "ticker": "^UTY"},
+    "w5klcg": {"name": "Wilshire US Large Cap Growth Index", "ticker": "^W5KLCG"},
+    "w5klcv": {"name": "Wilshire US Large Cap Value Index", "ticker": "^W5KLCV"},
+    "reit_wgreit": {"name": "Wilshire Global REIT Index", "ticker": "^WGREIT"},
+    "reit_wgresi": {
+        "name": "Wilshire Global Real Estate Sector Index",
+        "ticker": "^WGRESI",
+    },
+    "reit_wilreit": {"name": "Wilshire US REIT Index", "ticker": "^WILREIT"},
+    "reit_wilresi": {
+        "name": "Wilshire US Real Estate Security Index",
+        "ticker": "^WILRESI",
+    },
+    "cboe_bxm": {"name": "CBOE Buy-Write Monthly Index", "ticker": "^BXM"},
+    "cboe_vix": {"name": "CBOE S&P 500 Volatility Index", "ticker": "^VIX"},
+    "cboe_vix9d": {"name": "CBOE S&P 500 9-Day Volatility Index", "ticker": "^VIX9D"},
+    "cboe_vix3m": {"name": "CBOE S&P 500 3-Month Volatility Index", "ticker": "^VIX3M"},
+    "cboe_vin": {"name": "CBOE Near-Term VIX Index", "ticker": "^VIN"},
+    "cboe_vvix": {"name": "CBOE VIX Volatility Index", "ticker": "^VVIX"},
+    "cboe_shortvol": {"name": "CBOE Short VIX Futures Index", "ticker": "^SHORTVOL"},
+    "cboe_skew": {"name": "CBOE Skew Index", "ticker": "^SKEW"},
+    "cboe_vxn": {"name": "CBOE NASDAQ 100 Volatility Index", "ticker": "^VXN"},
+    "cboe_gvz": {"name": "CBOE Gold Volatility Index", "ticker": "^GVZ"},
+    "cboe_ovx": {"name": "CBOE Crude Oil Volatility Index", "ticker": "^OVX"},
+    "cboe_tnx": {"name": "CBOE Interest Rate 10 Year T-Note", "ticker": "^TNX"},
+    "cboe_tyx": {"name": "CBOE 30 year Treasury Yields", "ticker": "^TYX"},
+    "cboe_irx": {"name": "CBOE 13 Week Treasury Bill", "ticker": "^IRX"},
+    "cboe_evz": {"name": "CBOE Euro Currency Volatility Index", "ticker": "^EVZ"},
+    "cboe_rvx": {"name": "CBOE Russell 2000 Volatility Index", "ticker": "^RVX"},
+    "move": {"name": "ICE BofAML Move Index", "ticker": "^MOVE"},
+    "dxy": {"name": "US Dollar Index", "ticker": "DX-Y.NYB"},
+    "crypto200": {"name": "CMC Crypto 200 Index by Solacti", "ticker": "^CMC200"},
+}
diff --git a/openbb_sdk/pyproject.toml b/openbb_sdk/pyproject.toml
index cbedd4fb8f8..573fc94e1b2 100644
--- a/openbb_sdk/pyproject.toml
+++ b/openbb_sdk/pyproject.toml
@@ -13,6 +13,7 @@ openbb-core = { path = "./sdk/core" }
 openbb-benzinga = { path = "./providers/benzinga" }
 openbb-fmp = { path = "./providers/fmp" }
 openbb-fred = { path = "./providers/fred" }
+openbb-intrinio = { path = "./providers/intrinio" }
 openbb-polygon = { path = "./providers/polygon" }
 
 openbb-crypto = { path = "./extensions/crypto" }
@@ -23,7 +24,9 @@ openbb-news = { path = "./extensions/news" }
 openbb-stocks = { path = "./extensions/stocks" }
 
 # Community dependencies
+openbb-alpha-vantage = { path = "./providers/alpha_vantage", optional = true }
 openbb-cboe = { path = "./providers/cboe", optional = true }
+openbb-quandl = { path = "./providers/quandl", optional = true }
 openbb-yfinance = { path = "./providers/yfinance", optional = true }
 
 openbb-charting = { path = "./extensions/charting", optional = true }
@@ -32,7 +35,9 @@ openbb-qa = { path = "./extensions/qa", optional = true }
 openbb-ta = { path = "./extensions/ta", optional = true }
 
 [tool.poetry.extras]
+alpha_vantage = ["openbb-alpha-vantage"]
 cboe = ["openbb-cboe"]
+quandl = ["openbb-quandl"]
 yfinance = ["openbb-yfinance"]
 charting = ["openbb-charting"]
 futures = ["openbb-futures"]
@@ -40,7 +45,9 @@ qa = ["openbb-qa"]
 ta = ["openbb-ta"]
 
 all = [
+    "openbb-alpha-vantage",
     "openbb-cboe",
+    "openbb-quandl",
     "openbb-yfinance",
     "openbb-charting",
     "openbb-futures",
diff --git a/openbb_sdk/sdk/core/README.md b/openbb_sdk/sdk/core/README.md
index d11536c8e3a..7ad9515c4c7 100644
--- a/openbb_sdk/sdk/core/README.md
+++ b/openbb_sdk/sdk/core/README.md
@@ -78,10 +78,10 @@ def some_command(
 
 If your command only makes use of a standard model defined inside `openbb_provider/standard_models` directory, there is no need to repeat its structure in the parameters. Just pass the model name as an argument.
 
-This is an example how we do it for `stocks.load` which only depends on `StockEOD` model defined in `openbb-provider`:
+This is an example how we do it for `stocks.load` which only depends on `StockHistorical` model defined in `openbb-provider`:
 
 ```python
-@router.command(model="StockEOD")
+@router.command(model="StockHistorical")
 def load(
     cc: CommandContext,                 # user settings inside
     provider_choices: ProviderChoices,  # available providers
diff --git a/openbb_sdk/sdk/core/openbb_core/app/provider_interface.py b/openbb_sdk/sdk/core/openbb_core/app/provider_interface.py
index 706acebde38..e142f8ef732 100644
--- a/openbb_sdk/sdk/core/openbb_core/app/provider_interface.py
+++ b/openbb_sdk/sdk/core/openbb_core/app/provider_interface.py
@@ -390,7 +390,7 @@ class ProviderInterface(metaclass=SingletonMeta):
 
         Example:
         -------
-        class StockEODData(StandardData):
+        class StockHistoricalData(StandardData):
             date: date
             open: PositiveFloat
             high: PositiveFloat
diff --git a/openbb_sdk/sdk/core/tests/app/test_provider_interface.py b/openbb_sdk/sdk/core/tests/app/test_provider_interface.py
index 0e11fbf5a92..070a743bfdf 100644
--- a/openbb_sdk/sdk/core/tests/app/test_provider_interface.py
+++ b/openbb_sdk/sdk/core/tests/app/test_provider_interface.py
@@ -24,7 +24,7 @@ def test_map(provider_interface):
     provider_interface_map = provider_interface.map
     assert isinstance(provider_interface_map, dict)
     assert len(provider_interface_map) > 0
-    assert "StockEOD" in provider_interface_map
+    assert "StockHistorical" in provider_interface_map
 
 
 def test_required_credentials(provider_interface):
@@ -46,7 +46,7 @@ def test_params(provider_interface):
     params = provider_interface.params
     assert isinstance(params, dict)
     assert len(params) > 0
-    assert "StockEOD" in params
+    assert "StockHistorical" in params
 
 
 def test_data(provider_interface):
@@ -54,7 +54,7 @@ def test_data(provider_interface):
     data = provider_interface.data
     assert isinstance(data, dict)
     assert len(data) > 0
-    assert "StockEOD" in data
+    assert "StockHistorical" in data
 
 
 def test_available_providers(provider_interface):
@@ -76,4 +76,4 @@ def test_models(provider_interface):
     models = provider_interface.models
     assert isinstance(models, list)
     assert len(models) > 0
-    assert "StockEOD" in models
+    assert "StockHistorical" in models
diff --git a/openbb_sdk/sdk/core/tests/app/test_query.py b/openbb_sdk/sdk/core/tests/app/test_query.py
index ef32c0b048a..1aa692634f4 100644
--- a/openbb_sdk/sdk/core/tests/app/test_query.py
+++ b/openbb_sdk/sdk/core/tests/app/test_query.py
@@ -18,26 +18,26 @@ from pydantic import BaseModel
 def create_mock_query():
     """Mock query."""
 
-    class StockEOD:
-        """Mock StockEOD class."""
+    class StockHistorical:
+        """Mock StockHistorical class."""
 
         start_date = "2020-01-01"
         end_date = "2020-01-05"
         symbol = "AAPL"
 
-    return StockEOD()
+    return StockHistorical()
 
 
 def create_mock_extra_params():
     """Mock ExtraParams dataclass."""
 
     @dataclass
-    class StockEOD:
+    class StockHistorical:
         """Mock ExtraParams dataclass."""
 
         sort: str = "desc"
 
-    return StockEOD()
+    return StockHistorical()
 
 
 @pytest.fixture(scope="module")
@@ -69,13 +69,13 @@ def test_filter_extra_params_wrong_param(query):
     """Test filter_extra_params."""
 
     @dataclass
-    class StockEOD:
+    class StockHistorical:
         """Mock ExtraParams dataclass."""
 
         sort: str = "desc"
         limit: int = 4
 
-    extra_params = StockEOD()
+    extra_params = StockHistorical()
 
     assert not query.filter_extra_params(extra_params, "fmp")
 
diff --git a/openbb_sdk/sdk/core/tests/app/test_router.py b/openbb_sdk/sdk/core/tests/app/test_router.py
index 56f68538f92..aef94bfdcd5 100644
--- a/openbb_sdk/sdk/core/tests/app/test_router.py
+++ b/openbb_sdk/sdk/core/tests/app/test_router.py
@@ -187,7 +187,7 @@ def test_complete_signature(signature_inspector):
     ) -> OBBject:
         pass
 
-    model = "StockEOD"
+    model = "StockHistorical"
 
     assert signature_inspector.complete_signature(sample_function, model)
 
diff --git a/openbb_sdk/sdk/core/tests/test_query.py b/openbb_sdk/sdk/core/tests/test_query.py
index ef32c0b048a..1aa692634f4 100644
--- a/openbb_sdk/sdk/core/tests/test_query.py
+++ b/openbb_sdk/sdk/core/tests/test_query.py
@@ -18,26 +18,26 @@ from pydantic import BaseModel
 def create_mock_query():
     """Mock query."""
 
-    class StockEOD:
-        """Mock StockEOD class."""
+    class StockHistorical:
+        """Mock StockHistorical class."""
 
         start_date = "2020-01-01"
         end_date = "2020-01-05"
         symbol = "AAPL"
 
-    return StockEOD()
+    return StockHistorical()
 
 
 def create_mock_extra_params():
     """Mock ExtraParams dataclass."""
 
     @dataclass
-    class StockEOD:
+    class StockHistorical:
         """Mock ExtraParams dataclass."""
 
         sort: str = "desc"
 
-    return StockEOD()
+    return StockHistorical()
 
 
 @pytest.fixture(scope="module")
@@ -69,13 +69,13 @@ def test_filter_extra_params_wrong_param(query):
     """Test filter_extra_params."""
 
     @dataclass
-    class StockEOD:
+    class StockHistorical:
         """Mock ExtraParams dataclass."""
 
         sort: str = "desc"
         limit: int = 4
 
-    extra_params = StockEOD()
+    extra_params = StockHistorical()
 
     assert not query.filter_extra_params(extra_params, "fmp")
 
diff --git a/openbb_sdk/sdk/provider/openbb_provider/query_executor.py b/openbb_sdk/sdk/provider/openbb_provider/query_executor.py
index cb77cd653b7..9bb97fb5340 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/query_executor.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/query_executor.py
@@ -61,7 +61,7 @@ class QueryExecutor:
         provider_name : str
             Name of the provider, for example: "fmp".
         model_name : str
-            Name of the model, for example: "StockEOD".
+            Name of the model, for example: "StockHistorical".
         params : Dict[str, Any]
             Query parameters, for example: {"symbol": "AAPL"}
         credentials : Optional[Dict[str, str]], optional
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/available_indices.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/available_indices.py
index a199adf0ef9..728c937b7b9 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/standard_models/available_indices.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/available_indices.py
@@ -7,22 +7,17 @@ from pydantic import Field
 
 from openbb_provider.abstract.data import Data
 from openbb_provider.abstract.query_params import QueryParams
-from openbb_provider.standard_models.base import BaseSymbol
 
 
 class AvailableIndicesQueryParams(QueryParams):
     """Available Indices Query."""
 
 
-class AvailableIndicesData(Data, BaseSymbol):
+class AvailableIndicesData(Data):
     """Available Indices Data.
 
-    Returns the major indices from Dow Jones, Nasdaq and, S&P 500.
+    Returns the list of available indices from a provider.
     """
 
     name: Optional[str] = Field(description="Name of the index.")
     currency: Optional[str] = Field(description="Currency the index is traded in.")
-    stock_exchange: str = Field(description="Stock exchange where the index is listed.")
-    exchange_short_name: str = Field(
-        description="Short name of the stock exchange where the index is listed."
-    )
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/balance_sheet.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/balance_sheet.py
index 8093cad0043..787f6949534 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/standard_models/balance_sheet.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/balance_sheet.py
@@ -1,93 +1,108 @@
 """Balance Sheet Data Model."""
 
 
-from datetime import (
-    date as dateType,
-    datetime,
-)
+from datetime import date as dateType
 from typing import Optional
 
 from pydantic import Field
 
 from openbb_provider.abstract.data import Data
-from openbb_provider.standard_models.base import FinancialStatementQueryParams
-
-# IMPORT THIRD PARTY
+from openbb_provider.standard_models.base import (
+    BaseSymbol,
+    FinancialStatementQueryParams,
+)
 
 
 class BalanceSheetQueryParams(FinancialStatementQueryParams):
     """Balance Sheet query."""
 
 
-class BalanceSheetData(Data):
+class BalanceSheetData(Data, BaseSymbol):
     """Balance Sheet Data."""
 
     date: dateType = Field(description="Date of the fetched statement.")
-    symbol: Optional[str] = Field(description="Symbol of the company.")
-    cik: Optional[int] = Field(description="Central Index Key.")
-    currency: Optional[str] = Field(description="Reporting currency.")
-    filing_date: Optional[dateType] = Field(description="Filling date.")
-    accepted_date: Optional[datetime] = Field(description="Accepted date.")
     period: Optional[str] = Field(description="Reporting period of the statement.")
+    cik: Optional[int] = Field(description="Central Index Key (CIK) of the company.")
 
     cash_and_cash_equivalents: Optional[int] = Field(
         description="Cash and cash equivalents"
     )
     short_term_investments: Optional[int] = Field(description="Short-term investments")
-    inventory: Optional[int] = Field(description="Inventory")
     net_receivables: Optional[int] = Field(description="Receivables, net")
+    inventory: Optional[int] = Field(description="Inventory")
     other_current_assets: Optional[int] = Field(description="Other current assets")
-    current_assets: Optional[int] = Field(description="Total current assets")
+    total_current_assets: Optional[int] = Field(description="Total current assets")
 
-    long_term_investments: Optional[int] = Field(description="Long-term investments")
+    marketable_securities: Optional[int] = Field(description="Marketable securities")
     property_plant_equipment_net: Optional[int] = Field(
         description="Property, plant and equipment, net"
     )
     goodwill: Optional[int] = Field(description="Goodwill")
     intangible_assets: Optional[int] = Field(description="Intangible assets")
+    tax_assets: Optional[int] = Field(description="Accrued income taxes")
     other_non_current_assets: Optional[int] = Field(
         description="Other non-current assets"
     )
-    tax_assets: Optional[int] = Field(description="Accrued income taxes")
-    other_assets: Optional[int] = Field(description="Other assets")
-    noncurrent_assets: Optional[int]
-    assets: Optional[int]
-
-    account_payables: Optional[int]
-    other_current_liabilities: Optional[int]
-    tax_payables: Optional[int] = Field(description="Accrued income taxes")
-    deferred_revenue: Optional[int] = Field(
-        description="Accrued income taxes, other deferred revenue"
+    total_non_current_assets: Optional[int] = Field(
+        description="Total non-current assets"
     )
+    other_assets: Optional[int] = Field(description="Other assets")
+    total_assets: Optional[int] = Field(description="Total assets")
+
+    account_payables: Optional[int] = Field(description="Accounts payables")
     short_term_debt: Optional[int] = Field(
         description="Short-term borrowings, Long-term debt due within one year, "
         "Operating lease obligations due within one year, "
         "Finance lease obligations due within one year"
     )
-    current_liabilities: Optional[int]
+    tax_payables: Optional[int] = Field(description="Accrued income taxes")
+    deferred_revenue: Optional[int] = Field(
+        description="Accrued income taxes, other deferred revenue"
+    )
+    other_current_liabilities: Optional[int] = Field(
+        description="Other current liabilities"
+    )
+    total_current_liabilities: Optional[int] = Field(
+        description="Total current liabilities"
+    )
 
     long_term_debt: Optional[int] = Field(
-        description="Long-term debt, Operating lease obligations, Long-term finance lease obligations"
+        description="Long-term debt, Operating lease obligations, "
+        "Long-term finance lease obligations"
+    )
+    deferred_revenue_non_current: Optional[int] = Field(
+        description="Deferred revenue, non-current"
+    )
+    deferred_tax_liabilities_non_current: Optional[int] = Field(
+        description="Deferred income taxes and other"
     )
     other_non_current_liabilities: Optional[int] = Field(
         description="Deferred income taxes and other"
     )
-    other_liabilities: Optional[int]
-    noncurrent_liabilities: Optional[int]
-    liabilities: Optional[int]
-
-    common_stock: Optional[int]
-    other_stockholder_equity: Optional[int] = Field(
-        description="Capital in excess of par value"
+    total_non_current_liabilities: Optional[int] = Field(
+        description="Total non-current liabilities"
     )
+    other_liabilities: Optional[int] = Field(description="Other liabilities")
+    total_liabilities: Optional[int] = Field(description="Total liabilities")
 
+    preferred_stock: Optional[int] = Field(description="Preferred stock")
+    common_stock: Optional[int] = Field(description="Common stock")
+    retained_earnings: Optional[int] = Field(description="Retained earnings")
     accumulated_other_comprehensive_income_loss: Optional[int] = Field(
         description="Accumulated other comprehensive income (loss)"
     )
-    preferred_stock: Optional[int] = Field(description="Preferred stock")
-    retained_earnings: Optional[int] = Field(description="Retained earnings")
+    other_shareholder_equity: Optional[int] = Field(
+        description="Other shareholder's equity"
+    )
+    total_shareholder_equity: Optional[int] = Field(
+        description="Total shareholder's equity"
+    )
+
+    total_equity: Optional[int] = Field(description="Total equity")
+    total_liabilities_and_shareholders_equity: Optional[int] = Field(
+        description="Total liabilities and shareholder's equity"
+    )
     minority_interest: Optional[int] = Field(description="Minority interest")
-    total_stockholders_equity: Optional[int]
-    total_equity: Optional[int]
-    total_liabilities_and_stockholders_equity: Optional[int]
-    total_liabilities_and_total_equity: Optional[int]
+    total_liabilities_and_total_equity: Optional[int] = Field(
+        description="Total liabilities and total equity"
+    )
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/cash_flow.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/cash_flow.py
new file mode 100644
index 00000000000..33834ad03c4
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/cash_flow.py
@@ -0,0 +1,98 @@
+"""Cash Flow Statement Data Model."""
+
+
+from datetime import date as dateType
+from typing import Optional
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.standard_models.base import (
+    BaseSymbol,
+    FinancialStatementQueryParams,
+)
+
+
+class CashFlowStatementQueryParams(FinancialStatementQueryParams):
+    """Cash Flow Statement Query."""
+
+
+class CashFlowStatementData(Data, BaseSymbol):
+    """Cash Flow Statement Data."""
+
+    date: dateType = Field(description="Date of the fetched statement.")
+    period: Optional[str] = Field(description="Reporting period of the statement.")
+    cik: Optional[int] = Field(description="Central Index Key (CIK) of the company.")
+
+    net_income: Optional[int] = Field(description="Net income.")
+
+    depreciation_and_amortization: Optional[int] = Field(
+        description="Depreciation and amortization."
+    )
+    stock_based_compensation: Optional[int] = Field(
+        description="Stock based compensation."
+    )
+    deferred_income_tax: Optional[int] = Field(description="Deferred income tax.")
+    other_non_cash_items: Optional[int] = Field(description="Other non-cash items.")
+    changes_in_operating_assets_and_liabilities: Optional[int] = Field(
+        description="Changes in operating assets and liabilities."
+    )
+
+    accounts_receivables: Optional[int] = Field(description="Accounts receivables.")
+    inventory: Optional[int] = Field(description="Inventory.")
+    vendor_non_trade_receivables: Optional[int] = Field(
+        description="Vendor non-trade receivables."
+    )
+    other_current_and_non_current_assets: Optional[int] = Field(
+        description="Other current and non-current assets."
+    )
+    accounts_payables: Optional[int] = Field(description="Accounts payables.")
+    deferred_revenue: Optional[int] = Field(description="Deferred revenue.")
+    other_current_and_non_current_liabilities: Optional[int] = Field(
+        description="Other current and non-current liabilities."
+    )
+    net_cash_flow_from_operating_activities: Optional[int] = Field(
+        description="Net cash flow from operating activities."
+    )
+
+    purchases_of_marketable_securities: Optional[int] = Field(
+        description="Purchases of investments."
+    )
+    sales_from_maturities_of_investments: Optional[int] = Field(
+        description="Sales and maturities of investments."
+    )
+    investments_in_property_plant_and_equipment: Optional[int] = Field(
+        description="Investments in property, plant, and equipment."
+    )
+    payments_from_acquisitions: Optional[int] = Field(
+        description="Acquisitions, net of cash acquired, and other"
+    )
+    other_investing_activities: Optional[int] = Field(
+        description="Other investing activities"
+    )
+    net_cash_flow_from_investing_activities: Optional[int] = Field(
+        description="Net cash used for investing activities."
+    )
+
+    taxes_paid_on_net_share_settlement: Optional[int] = Field(
+        description="Taxes paid on net share settlement of equity awards."
+    )
+    dividends_paid: Optional[int] = Field(
+        description="Payments for dividends and dividend equivalents"
+    )
+    common_stock_repurchased: Optional[int] = Field(
+        description="Payments related to repurchase of common stock"
+    )
+    debt_proceeds: Optional[int] = Field(
+        description="Proceeds from issuance of term debt"
+    )
+    debt_repayment: Optional[int] = Field(description="Payments of long-term debt")
+    other_financing_activities: Optional[int] = Field(
+        description="Other financing activities, net"
+    )
+    net_cash_flow_from_financing_activities: Optional[int] = Field(
+        description="Net cash flow from financing activities."
+    )
+    net_change_in_cash: Optional[int] = Field(
+        description="Net increase (decrease) in cash, cash equivalents, and restricted cash"
+    )
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/cot_search.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/cot_search.py
new file mode 100644
index 00000000000..474a1909365
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/cot_search.py
@@ -0,0 +1,29 @@
+"""Commitment of Traders Reports Search  data model."""
+
+from typing import Optional
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+
+
+class CotSearchQueryParams(QueryParams):
+    """Commitment of Traders Reports Search Query Params"""
+
+    query: str = Field(description="Search query.", default="")
+
+
+class CotSearchData(Data):
+    """Commitment of Traders Reports Search Data."""
+
+    code: str = Field(description="CFTC Code of the report.")
+    name: str = Field(description="Name of the underlying asset.")
+    category: Optional[str] = Field(description="Category of the underlying asset.")
+    subcategory: Optional[str] = Field(
+        description="Subcategory of the underlying asset."
+    )
+    units: Optional[str] = Field(description="The units for one contract.")
+    symbol: Optional[str] = Field(
+        description="Trading symbol representing the underlying asset."
+    )
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/crypto_historical.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/crypto_historical.py
new file mode 100644
index 00000000000..6113e3f4820
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/crypto_historical.py
@@ -0,0 +1,37 @@
+"""Crypto aggregate end of day price data model."""
+
+
+from datetime import date, datetime
+from typing import Optional
+
+from pydantic import Field, PositiveFloat
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+
+
+class CryptoHistoricalQueryParams(QueryParams, BaseSymbol):
+    """Crypto end of day Query."""
+
+    start_date: Optional[date] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("start_date", ""),
+    )
+    end_date: Optional[date] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("end_date", ""),
+    )
+
+
+class CryptoHistoricalData(Data):
+    """Crypto end of day price Data."""
+
+    date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
+    open: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("open", ""))
+    high: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("high", ""))
+    low: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("low", ""))
+    close: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("close", ""))
+    volume: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
+    vwap: Optional[PositiveFloat] = Field(description=DATA_DESCRIPTIONS.get("vwap", ""))
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/european_index_constituents.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/european_index_constituents.py
new file mode 100644
index 00000000000..754005e0b2c
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/european_index_constituents.py
@@ -0,0 +1,27 @@
+"""European Index Constituents data model."""
+
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS
+
+
+class EuropeanIndexConstituentsQueryParams(QueryParams, BaseSymbol):
+    """European Index Constituents Query."""
+
+
+class EuropeanIndexConstituentsData(Data):
+    """European Index Constituents data."""
+
+    symbol: str = Field(description="Symbol of the constituent company in the index.")
+    price: float = Field(
+        description="Current price of the constituent company in the index."
+    )
+    open: float = Field(description=DATA_DESCRIPTIONS.get("open", ""))
+    high: float = Field(description=DATA_DESCRIPTIONS.get("high", ""))
+    low: float = Field(description=DATA_DESCRIPTIONS.get("low", ""))
+    close: float = Field(description=DATA_DESCRIPTIONS.get("close", ""))
+    volume: float = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/european_index_historical.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/european_index_historical.py
new file mode 100644
index 00000000000..4d28832308b
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/european_index_historical.py
@@ -0,0 +1,33 @@
+"""European Indices End of Day data model."""
+
+
+from datetime import (
+    date as dateType,
+    datetime,
+)
+from typing import Optional
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+
+
+class EuropeanIndexHistoricalQueryParams(QueryParams, BaseSymbol):
+    """European Indices end of day Query."""
+
+    start_date: Optional[dateType] = Field(
+        description=QUERY_DESCRIPTIONS.get("start_date", ""), default=None
+    )
+    end_date: Optional[dateType] = Field(
+        description=QUERY_DESCRIPTIONS.get("end_date", ""), default=None
+    )
+
+
+class EuropeanIndexHistoricalData(Data):
+    """European Indices end of day price data."""
+
+    date: dateType | datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
+    close: float = Field(description=DATA_DESCRIPTIONS.get("close", ""))
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/forex_historical.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/forex_historical.py
new file mode 100644
index 00000000000..175f7db1d66
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/forex_historical.py
@@ -0,0 +1,37 @@
+"""Forex aggregate end of day price data model."""
+
+
+from datetime import date, datetime
+from typing import Optional
+
+from pydantic import Field, NonNegativeFloat, PositiveFloat
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+
+
+class ForexHistoricalQueryParams(QueryParams, BaseSymbol):
+    """Forex end of day Query."""
+
+    start_date: Optional[date] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("start_date", ""),
+    )
+    end_date: Optional[date] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("end_date", ""),
+    )
+
+
+class ForexHistoricalData(Data):
+    """Forex end of day price Data."""
+
+    date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
+    open: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("open", ""))
+    high: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("high", ""))
+    low: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("low", ""))
+    close: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("close", ""))
+    volume: NonNegativeFloat = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
+    vwap: Optional[PositiveFloat] = Field(description=DATA_DESCRIPTIONS.get("vwap", ""))
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/futures_historical.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/futures_historical.py
new file mode 100644
index 00000000000..f353a575081
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/futures_historical.py
@@ -0,0 +1,40 @@
+"""Futures aggregate end of day price data model."""
+
+
+from datetime import date, datetime
+from typing import Optional
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+
+
+class FuturesHistoricalQueryParams(QueryParams, BaseSymbol):
+    """Futures end of day Query."""
+
+    start_date: Optional[date] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("start_date", ""),
+    )
+    end_date: Optional[date] = Field(
+        default=None,
+        description=QUERY_DESCRIPTIONS.get("end_date", ""),
+    )
+    expiration: Optional[str] = Field(
+        default=None,
+        description="Future expiry date with format YYYY-MM",
+    )
+
+
+class FuturesHistoricalData(Data):
+    """Futures end of day price Data."""
+
+    date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
+    open: float = Field(description=DATA_DESCRIPTIONS.get("open", ""))
+    high: float = Field(description=DATA_DESCRIPTIONS.get("high", ""))
+    low: float = Field(description=DATA_DESCRIPTIONS.get("low", ""))
+    close: float = Field(description=DATA_DESCRIPTIONS.get("close", ""))
+    volume: float = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/income_statement.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/income_statement.py
index 4501ea886b9..d897712f4c5 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/standard_models/income_statement.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/income_statement.py
@@ -1,34 +1,28 @@
 """Income Statement Data Model."""
 
 
-from datetime import (
-    date as dateType,
-    datetime,
-)
+from datetime import date as dateType
 from typing import Optional
 
 from pydantic import Field
 
 from openbb_provider.abstract.data import Data
-from openbb_provider.standard_models.base import FinancialStatementQueryParams
+from openbb_provider.standard_models.base import (
+    BaseSymbol,
+    FinancialStatementQueryParams,
+)
 
 
 class IncomeStatementQueryParams(FinancialStatementQueryParams):
     """Income Statement Query."""
 
 
-class IncomeStatementData(Data):
+class IncomeStatementData(Data, BaseSymbol):
     """Income Statement Data."""
 
     date: dateType = Field(description="Date of the income statement.")
-    symbol: str = Field(description="Symbol of the company.")
-    cik: Optional[str] = Field(description="Central Index Key.")
-
-    currency: Optional[str] = Field(description="Reporting currency.")
-    filing_date: Optional[dateType] = Field(description="Filling date.")
-    accepted_date: Optional[datetime] = Field(description="Accepted date.")
-    calendar_year: Optional[int] = Field(description="Calendar year.")
-    period: Optional[str] = Field(description="Period of the income statement.")
+    period: str = Field(description="Period of the income statement.")
+    cik: str = Field(description="Central Index Key.")
 
     revenue: Optional[int] = Field(description="Revenue.")
     cost_of_revenue: Optional[int] = Field(description="Cost of revenue.")
@@ -87,5 +81,3 @@ class IncomeStatementData(Data):
     weighted_average_shares_outstanding_dil: Optional[int] = Field(
         description="Weighted average shares outstanding diluted."
     )
-    link: Optional[str] = Field(description="Link to the income statement.")
-    final_link: Optional[str] = Field(description="Final link to the income statement.")
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/index_search.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/index_search.py
new file mode 100644
index 00000000000..14ae4cc4702
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/index_search.py
@@ -0,0 +1,22 @@
+"""Index Search  data model."""
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+
+
+class IndexSearchQueryParams(QueryParams):
+    """Index Search Query Params"""
+
+    query: str = Field(description="Search query.", default="")
+    symbol: bool = Field(
+        description="Whether to search by ticker symbol.", default=False
+    )
+
+
+class IndexSearchData(Data):
+    """Company Search Data."""
+
+    symbol: str = Field(description="Symbol of the index.")
+    name: str = Field(description="Name of the index.")
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/index_snapshots.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/index_snapshots.py
new file mode 100644
index 00000000000..23c556e3406
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/index_snapshots.py
@@ -0,0 +1,34 @@
+"""Index Snapshots  data model."""
+
+from typing import Literal, Optional
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+
+
+class IndexSnapshotsQueryParams(QueryParams):
+    """Index Search Query Params"""
+
+    region: Optional[Literal["US", "EU"]] = Field(
+        description="The region to return. Currently supports US and EU.", default="US"
+    )
+
+
+class IndexSnapshotsData(Data):
+    """Index Snapshot Data."""
+
+    symbol: str = Field(description="Symbol of the index.")
+    name: Optional[str] = Field(description="Name of the index.")
+    currency: Optional[str] = Field(description="Currency of the index.")
+    price: Optional[float] = Field(description="Current price of the index.")
+    open: Optional[float] = Field(description="Opening price of the index.")
+    high: Optional[float] = Field(description="Highest price of the index.")
+    low: Optional[float] = Field(description="Lowest price of the index.")
+    close: Optional[float] = Field(description="Closing price of the index.")
+    prev_close: Optional[float] = Field(
+        description="Previous closing price of the index."
+    )
+    change: Optional[float] = Field(description="Change of the index.")
+    change_percent: Optional[float] = Field(description="Change percent of the index.")
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/major_indices_historical.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/major_indices_historical.py
new file mode 100644
index 00000000000..e209ec3eb15
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/major_indices_historical.py
@@ -0,0 +1,39 @@
+"""Major indices aggregate end of day price data model."""
+
+
+from datetime import (
+    date as dateType,
+    datetime,
+)
+from typing import Optional
+
+from pydantic import Field, NonNegativeInt, PositiveFloat
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+
+
+class MajorIndicesHistoricalQueryParams(QueryParams, BaseSymbol):
+    """Major Indices end of day Query."""
+
+    start_date: Optional[dateType] = Field(
+        description=QUERY_DESCRIPTIONS.get("start_date", ""), default=None
+    )
+    end_date: Optional[dateType] = Field(
+        description=QUERY_DESCRIPTIONS.get("end_date", ""), default=None
+    )
+
+
+class MajorIndicesHistoricalData(Data):
+    """Major Indices end of day price data."""
+
+    date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
+    open: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("open", ""))
+    high: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("high", ""))
+    low: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("low", ""))
+    close: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("close", ""))
+    volume: Optional[NonNegativeInt] = Field(
+        description=DATA_DESCRIPTIONS.get("volume", "")
+    )
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/options_chains.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/options_chains.py
index f39c252c745..105ea8fe977 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/standard_models/options_chains.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/options_chains.py
@@ -19,6 +19,7 @@ class OptionsChainsData(Data):
     expiration: datetime = Field(description="Expiration date of the contract.")
     strike: float = Field(description="Strike price of the contract.")
     option_type: str = Field(description="Call or Put.")
+    contract_symbol: str = Field(description="Contract symbol for the option.")
     bid: float = Field(description="Bid price of the contract.")
     ask: float = Field(description="Ask price of the contract.")
     open_interest: float = Field(description="Open interest on the contract.")
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/sp500_multiples.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/sp500_multiples.py
new file mode 100644
index 00000000000..d17309c3aac
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/sp500_multiples.py
@@ -0,0 +1,77 @@
+"""SP500 Multiples Data model."""
+
+from typing import Literal, Optional
+
+from pydantic import Field
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+
+
+class SP500MultiplesQueryParams(QueryParams):
+    """Gets historical S&P 500 levels, ratios, and multiples."""
+
+    series_name: Literal[
+        "Shiller PE Ratio by Month",
+        "Shiller PE Ratio by Year",
+        "PE Ratio by Year",
+        "PE Ratio by Month",
+        "Dividend by Year",
+        "Dividend by Month",
+        "Dividend Growth by Quarter",
+        "Dividend Growth by Year",
+        "Dividend Yield by Year",
+        "Dividend Yield by Month",
+        "Earnings by Year",
+        "Earnings by Month",
+        "Earnings Growth by Year",
+        "Earnings Growth by Quarter",
+        "Real Earnings Growth by Year",
+        "Real Earnings Growth by Quarter",
+        "Earnings Yield by Year",
+        "Earnings Yield by Month",
+        "Real Price by Year",
+        "Real Price by Month",
+        "Inflation Adjusted Price by Year",
+        "Inflation Adjusted Price by Month",
+        "Sales by Year",
+        "Sales by Quarter",
+        "Sales Growth by Year",
+        "Sales Growth by Quarter",
+        "Real Sales by Year",
+        "Real Sales by Quarter",
+        "Real Sales Growth by Year",
+        "Real Sales Growth by Quarter",
+        "Price to Sales Ratio by Year",
+        "Price to Sales Ratio by Quarter",
+        "Price to Book Value Ratio by Year",
+        "Price to Book Value Ratio by Quarter",
+        "Book Value per Share by Year",
+        "Book Value per Share by Quarter",
+    ] = Field(
+        description="The name of the series. Defaults to 'PE Ratio by Month'.",
+        default="PE Ratio by Month",
+    )
+    start_date: Optional[str] = Field(
+        description="The start date of the time series. Format: YYYY-MM-DD", default=""
+    )
+    end_date: Optional[str] = Field(
+        description="The end date of the time series. Format: YYYY-MM-DD", default=""
+    )
+    collapse: Optional[
+        Literal["daily", "weekly", "monthly", "quarterly", "annual"]
+    ] = Field(
+        description="Collapse the frequency of the time series.",
+        default="monthly",
+    )
+    transform: Optional[Literal["diff", "rdiff", "cumul", "normalize"]] = Field(
+        description="The transformation of the time series.",
+        default=None,
+    )
+
+
+class SP500MultiplesData(Data):
+    """SP500 Multiples Data."""
+
+    date: str = Field(description="The date data for the time series.")
+    value: float = Field(description="The data value for the time series.")
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_historical.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_historical.py
new file mode 100644
index 00000000000..2d8832a5b12
--- /dev/null
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_historical.py
@@ -0,0 +1,38 @@
+"""Stock aggregate end of day price data model."""
+
+
+from datetime import (
+    date as dateType,
+    datetime,
+)
+from typing import Optional
+
+from pydantic import Field, NonNegativeInt, PositiveFloat
+
+from openbb_provider.abstract.data import Data
+from openbb_provider.abstract.query_params import QueryParams
+from openbb_provider.standard_models.base import BaseSymbol
+from openbb_provider.utils.descriptions import DATA_DESCRIPTIONS, QUERY_DESCRIPTIONS
+
+
+class StockHistoricalQueryParams(QueryParams, BaseSymbol):
+    """Stock end of day Query."""
+
+    start_date: Optional[dateType] = Field(
+        description=QUERY_DESCRIPTIONS.get("start_date", ""), default=None
+    )
+    end_date: Optional[dateType] = Field(
+        description=QUERY_DESCRIPTIONS.get("end_date", ""), default=None
+    )
+
+
+class StockHistoricalData(Data):
+    """Stock end of day price Data."""
+
+    date: datetime = Field(description=DATA_DESCRIPTIONS.get("date", ""))
+    open: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("open", ""))
+    high: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("high", ""))
+    low: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("low", ""))
+    close: PositiveFloat = Field(description=DATA_DESCRIPTIONS.get("close", ""))
+    volume: NonNegativeInt = Field(description=DATA_DESCRIPTIONS.get("volume", ""))
+    vwap: Optional[PositiveFloat] = Field(description=DATA_DESCRIPTIONS.get("vwap", ""))
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_info.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_info.py
index 44cf141dfc4..c91583f90c0 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_info.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_info.py
@@ -17,17 +17,15 @@ class StockInfoData(Data, BaseSymbol):
     """Stock Info Data."""
 
     name: str = Field(description="Name associated with the ticker symbol.")
-    price: float = Field(description="Last price of the stock.")
-    open: Optional[float] = Field(description="Opening price of the stock.")
-    high: Optional[float] = Field(description="High price of the current trading day.")
-    low: Optional[float] = Field(description="Low price of the current trading day.")
-    close: Optional[float] = Field(description="Closing price of the stock.")
+    price: float = Field(description="Last transaction price.")
+    open: float = Field(description="Opening price of the stock.")
+    high: float = Field(description="High price of the current trading day.")
+    low: float = Field(description="Low price of the current trading day.")
+    close: float = Field(description="Closing price of the most recent trading day.")
     change: Optional[float] = Field(
         description="Change in price over the current trading period."
     )
     change_percent: Optional[float] = Field(
-        description="% change in price over the current trading period."
-    )
-    previous_close: Optional[float] = Field(
-        description="Previous closing price of the stock."
+        description="Percent change in price over the current trading period."
     )
+    prev_close: Optional[float] = Field(description="Previous closing price.")
diff --git a/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_quote.py b/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_quote.py
index 81a5394ac16..e558edef441 100644
--- a/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_quote.py
+++ b/openbb_sdk/sdk/provider/openbb_provider/standard_models/stock_quote.py
@@ -27,13 +27,6 @@ class StockQuoteQueryParams(QueryParams, BaseSymbol):
 class StockQuoteData(Data):
     """Stock Quote data."""
 
-    symbol: str = Field(description="Symbol of the company.")
-    name: Optional[str] = Field(description="Name of the company.")
-    price: Optional[float] = Field(description="Current trading price of the stock.")
-    changes_percentage: Optional[float] = Field(
-        description="Change percentage of the stock price."
-    )
-    change: Optional[float] = Field(description="Change of the stock price.")
     day_low: Optional[float] = Field(
         default=None,
         description="Lowest price of the stock in the current trading day.",
@@ -42,42 +35,6 @@ class StockQuoteData(Data):
         default=None,
         description="Highest price of the stock in the current trading day.",
     )
-    year_high: Optional[float] = Field(
-        description="Highest price of the stock in the last 52 weeks."
-    )
-    year_low: Optional[float] = Field(
-        description="Lowest price of the stock in the last 52 weeks."
-    )
-    market_cap: Optional[float] = Field(description="Market cap of the company.")
-    price_avg50: Optional[float] = Field(
-        description="50 days average price of the stock."
-    )
-    price_avg200: Optional[float] = Field(
-        description="200 days average price of the stock."
-    )
-    volume: Optional[int] = Field(
-        description="Volume of the stock in the current trading day."
-    )
-    avg_volume: Optional[int] = Field(
-        default=None,
-        description="Average volume of the stock in the last 10 trading days.",
-    )
-    exchange: Optional[str] = Field(description="Exchange the stock is traded on.")
-    open: Optional[float] = Field(
-        default=None,
-        description="Opening price of the stock in the current trading day.",
-    )
-    previous_close: Optional[float] = Field(
-        description="Previous closing price of the stock."
-    )
-    eps: Optional[float] = Field(description="Earnings per share of the stock.")
-    pe: Optional[float] = Field(description="Price earnings ratio of the stock.")
-    earnings_announcement: Optional[str] = Field(
-        description="Earnings announcement date of the stock."
-    )
-    shares_outstanding: Optional[int] = Field(
-        description="Number of shares outstanding of the stock."
-    )
     date: Optional[datetime] = Field(
         description="Timestamp of the stock quote.", alias="timestamp"
     )