Incorporate portfolio class into SDK (#3401)

* create functions to interact with portfolio * fix some docstrings * view docstrings * make portfolio loading available in sdk * reorder some methods * fix bug * update controller * update website * remove import * change input name * regenerate website * change portfolio arg name * fix metrics bugs * fix report * refactor assets alloc * refactor assets sectors alloc * remove unecessary attributes * refactor allocaasset sector * reorganize class * first refactor alloc * refactor portfolio alloc * black * fix alloc bug * regenerate sdk website * fix alloc bugs * forgot this exception * some refactor on portfolio alloc country region * fix some allocation bugs * add examples * regenerate website Co-authored-by: James Maslek <jmaslek11@gmail.com>
2026-10-27 12:40:35 +00:00 · 2022-11-14 16:27:34 +00:00
parent 2b60a1cf38
commit 8e9e6bd57f
112 changed files with 3138 additions and 1629 deletions
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -681,7 +681,7 @@ With:
    transactions = Portfolio.read_orderbook("../../portfolio/holdings/example.csv")
    P = Portfolio(transactions)
    P.generate_portfolio_data()
-    P.load_benchmark()
+    P.set_benchmark()

    # SDK endpoint access
    openbb.portfolio.gaintopain(P)
@@ -695,7 +695,7 @@ With:
    <td>

    ```python
-    def get_gaintopain_ratio(portfolio: PortfolioModel) -> pd.DataFrame:
+    def get_gaintopain_ratio(portfolio: PortfolioEngine) -> pd.DataFrame:

    """..."""

--- a/openbb_terminal/miscellaneous/library/trail_map.csv
+++ b/openbb_terminal/miscellaneous/library/trail_map.csv
@@ -295,36 +295,42 @@ forex.oanda.listorders,openbb_terminal.forex.oanda.oanda_model.order_history_req
 forex.oanda.orderbook,openbb_terminal.forex.oanda.oanda_model.orderbook_plot_data_request,openbb_terminal.forex.oanda.oanda_view.get_order_book
 forex.oanda.pending,openbb_terminal.forex.oanda.oanda_model.pending_orders_request,openbb_terminal.forex.oanda.oanda_view.get_pending_orders
 forex.oanda.positionbook,openbb_terminal.forex.oanda.oanda_model.positionbook_plot_data_request,openbb_terminal.forex.oanda.oanda_view.get_position_book
+portfolio.load,openbb_terminal.portfolio.portfolio_model.generate_portfolio,
+portfolio.show,openbb_terminal.portfolio.portfolio_model.get_transactions,
+portfolio.bench,openbb_terminal.portfolio.portfolio_model.set_benchmark,
 portfolio.holdv,openbb_terminal.portfolio.portfolio_model.get_holdings_value,openbb_terminal.portfolio.portfolio_view.display_holdings_value
 portfolio.holdp,openbb_terminal.portfolio.portfolio_model.get_holdings_percentage,openbb_terminal.portfolio.portfolio_view.display_holdings_percentage
-portfolio.yret,openbb_terminal.portfolio.portfolio_model.get_yearly_returns,openbb_terminal.portfolio.portfolio_view.display_yearly_returns
 portfolio.mret,openbb_terminal.portfolio.portfolio_model.get_monthly_returns,openbb_terminal.portfolio.portfolio_view.display_monthly_returns
+portfolio.yret,openbb_terminal.portfolio.portfolio_model.get_yearly_returns,openbb_terminal.portfolio.portfolio_view.display_yearly_returns
 portfolio.dret,openbb_terminal.portfolio.portfolio_model.get_daily_returns,openbb_terminal.portfolio.portfolio_view.display_daily_returns
-portfolio.max_drawdown_ratio,openbb_terminal.portfolio.portfolio_model.get_maximum_drawdown,openbb_terminal.portfolio.portfolio_view.display_maximum_drawdown_ratio
 portfolio.distr,openbb_terminal.portfolio.portfolio_model.get_distribution_returns,openbb_terminal.portfolio.portfolio_view.display_distribution_returns
 portfolio.maxdd,openbb_terminal.portfolio.portfolio_model.get_maximum_drawdown,openbb_terminal.portfolio.portfolio_view.display_maximum_drawdown
 portfolio.rvol,openbb_terminal.portfolio.portfolio_model.get_rolling_volatility,openbb_terminal.portfolio.portfolio_view.display_rolling_volatility
 portfolio.rsharpe,openbb_terminal.portfolio.portfolio_model.get_rolling_sharpe,openbb_terminal.portfolio.portfolio_view.display_rolling_sharpe
-portfolio.rsortino,openbb_terminal.portfolio.portfolio_model.get_rolling_sortino,openbb_terminal.portfolio.portfolio_view.display_rolling_sortino
+portfolio.rsort,openbb_terminal.portfolio.portfolio_model.get_rolling_sortino,openbb_terminal.portfolio.portfolio_view.display_rolling_sortino
 portfolio.rbeta,openbb_terminal.portfolio.portfolio_model.get_rolling_beta,openbb_terminal.portfolio.portfolio_view.display_rolling_beta
 portfolio.summary,openbb_terminal.portfolio.portfolio_model.get_summary,
-portfolio.skew,openbb_terminal.portfolio.portfolio_model.get_skewness,
-portfolio.kurtosis,openbb_terminal.portfolio.portfolio_model.get_kurtosis,
-portfolio.volatility,openbb_terminal.portfolio.portfolio_model.get_volatility,
-portfolio.sharpe,openbb_terminal.portfolio.portfolio_model.get_sharpe_ratio,
-portfolio.sortino,openbb_terminal.portfolio.portfolio_model.get_sortino_ratio,
-portfolio.maxdrawdown,openbb_terminal.portfolio.portfolio_model.get_maximum_drawdown_ratio,
-portfolio.rsquare,openbb_terminal.portfolio.portfolio_model.get_r2_score,
-portfolio.gaintopain,openbb_terminal.portfolio.portfolio_model.get_gaintopain_ratio,
-portfolio.trackerr,openbb_terminal.portfolio.portfolio_model.get_tracking_error,
-portfolio.information,openbb_terminal.portfolio.portfolio_model.get_information_ratio,
-portfolio.tail,openbb_terminal.portfolio.portfolio_model.get_tail_ratio,
-portfolio.commonsense,openbb_terminal.portfolio.portfolio_model.get_common_sense_ratio,
-portfolio.jensens,openbb_terminal.portfolio.portfolio_model.get_jensens_alpha,
-portfolio.calmar,openbb_terminal.portfolio.portfolio_model.get_calmar_ratio,
-portfolio.kelly,openbb_terminal.portfolio.portfolio_model.get_kelly_criterion,
-portfolio.payoff,openbb_terminal.portfolio.portfolio_model.get_payoff_ratio,
-portfolio.profitfactor,openbb_terminal.portfolio.portfolio_model.get_profit_factor,
+portfolio.alloc.assets,openbb_terminal.portfolio.portfolio_model.get_assets_allocation,
+portfolio.alloc.sectors,openbb_terminal.portfolio.portfolio_model.get_sectors_allocation,
+portfolio.alloc.countries,openbb_terminal.portfolio.portfolio_model.get_countries_allocation,
+portfolio.alloc.regions,openbb_terminal.portfolio.portfolio_model.get_regions_allocation,
+portfolio.metric.volatility,openbb_terminal.portfolio.portfolio_model.get_volatility,
+portfolio.metric.sharpe,openbb_terminal.portfolio.portfolio_model.get_sharpe_ratio,
+portfolio.metric.sortino,openbb_terminal.portfolio.portfolio_model.get_sortino_ratio,
+portfolio.metric.maxdrawdown,openbb_terminal.portfolio.portfolio_model.get_maximum_drawdown_ratio,
+portfolio.metric.rsquare,openbb_terminal.portfolio.portfolio_model.get_r2_score,
+portfolio.metric.skew,openbb_terminal.portfolio.portfolio_model.get_skewness,
+portfolio.metric.kurtosis,openbb_terminal.portfolio.portfolio_model.get_kurtosis,
+portfolio.metric.gaintopain,openbb_terminal.portfolio.portfolio_model.get_gaintopain_ratio,
+portfolio.metric.trackerr,openbb_terminal.portfolio.portfolio_model.get_tracking_error,
+portfolio.metric.information,openbb_terminal.portfolio.portfolio_model.get_information_ratio,
+portfolio.metric.tail,openbb_terminal.portfolio.portfolio_model.get_tail_ratio,
+portfolio.metric.commonsense,openbb_terminal.portfolio.portfolio_model.get_common_sense_ratio,
+portfolio.metric.jensens,openbb_terminal.portfolio.portfolio_model.get_jensens_alpha,
+portfolio.metric.calmar,openbb_terminal.portfolio.portfolio_model.get_calmar_ratio,
+portfolio.metric.kelly,openbb_terminal.portfolio.portfolio_model.get_kelly_criterion,
+portfolio.metric.payoff,openbb_terminal.portfolio.portfolio_model.get_payoff_ratio,
+portfolio.metric.profitfactor,openbb_terminal.portfolio.portfolio_model.get_profit_factor,
 portfolio.perf,openbb_terminal.portfolio.portfolio_model.get_performance_vs_benchmark,
 portfolio.var,openbb_terminal.portfolio.portfolio_model.get_var,
 portfolio.es,openbb_terminal.portfolio.portfolio_model.get_es,
--- a/openbb_terminal/portfolio/allocation_model.py
+++ b/openbb_terminal/portfolio/allocation_model.py
@@ -1,5 +1,5 @@
 import logging
-from typing import Dict
+from typing import Dict, Tuple

 import pandas as pd
 import requests
@@ -12,22 +12,61 @@ logger = logging.getLogger(__name__)


@log_start_end(log=logger)
-def get_assets_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):
-    """Obtain the assets allocation of the benchmark and portfolio [Source: Yahoo Finance]
+def get_allocation(
+    category: str, benchmark_info: Dict, portfolio_trades: pd.DataFrame
+) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    """Get category allocation for benchmark and portfolio
+
+    Parameters
+    ----------
+    category: str
+        Chosen category: Asset, Sector, Country or Region
+    benchmark_info: Dict
+        Dictionary containing Yahoo Finance information
+    portfolio_trades: pd.DataFrame
+        Object containing trades made within the portfolio
+
+    Returns
+    -------
+    pd.DataFrame
+        DataFrame with the top 10 of the benchmark's asset allocations
+    pd.DataFrame
+        DataFrame with the portfolio's asset allocations
+    """
+
+    if category == "Asset":
+        return get_assets_allocation(benchmark_info, portfolio_trades)
+    if category == "Sector":
+        return get_sectors_allocation(benchmark_info, portfolio_trades)
+    if category == "Country":
+        return get_countries_allocation(benchmark_info, portfolio_trades)
+    if category == "Region":
+        return get_regions_allocation(benchmark_info, portfolio_trades)
+    console.print(
+        "Category not available. Choose from: Asset, Sector, Country or Region."
+    )
+    return pd.DataFrame(), pd.DataFrame()
+
+
+@log_start_end(log=logger)
+def get_assets_allocation(
+    benchmark_info: Dict, portfolio_trades: pd.DataFrame
+) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    """Get assets allocation for benchmark and portfolio [Source: Yahoo Finance]

    Parameters
    ----------
    benchmark_info: Dict
-        Dictionary containing Yahoo Finance information.
+        Dictionary containing Yahoo Finance information
    portfolio_trades: pd.DataFrame
-        Object containing trades made within the portfolio.
+        Object containing trades made within the portfolio

    Returns
    -------
-    benchmark_assets_allocation: dict
-        Dictionary with the top 10 of the benchmark's asset allocations.
-    portfolio_assets_allocation: dict
-        Dictionary with the portfolio's asset allocations
+    pd.DataFrame
+        DataFrame with the top 10 of the benchmark's asset allocations
+    pd.DataFrame
+        DataFrame with the portfolio's asset allocations
    """
    benchmark_assets_allocation = pd.DataFrame(benchmark_info["holdings"])
    benchmark_assets_allocation.rename(
@@ -51,26 +90,26 @@ def get_assets_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):


@log_start_end(log=logger)
-def get_sector_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):
-    """Obtain the sector allocation of the benchmark and portfolio [Source: Yahoo Finance]
+def get_sectors_allocation(
+    benchmark_info: Dict, portfolio_trades: pd.DataFrame
+) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    """Get sector allocation for benchmark and portfolio [Source: Yahoo Finance]

    Parameters
    ----------
    benchmark_info: Dict
-        Dictionary containing Yahoo Finance information.
+        Dictionary containing Yahoo Finance information
    portfolio_trades: pd.DataFrame
-        Object containing trades made within the portfolio.
+        Object containing trades made within the portfolio

    Returns
    -------
-    regional_allocation: dict
-        Dictionary with regional allocations.
-    country_allocation: dict
-        Dictionary with country allocations
+    pd.DataFrame
+        DataFrame with regional allocations.
+    pd.DataFrame
+        DataFrame with country allocations
    """

-    p_bar = tqdm(range(3), desc="Loading sector data")
-
    benchmark_sectors_allocation = (
        pd.DataFrame.from_dict(
            data={
@@ -91,6 +130,9 @@ def get_sector_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):
    ]

    benchmark_sectors_allocation.index = prettified
+    benchmark_sectors_allocation = pd.DataFrame(benchmark_sectors_allocation)
+    benchmark_sectors_allocation.reset_index(inplace=True)
+    benchmark_sectors_allocation.columns = ["Sector", "Benchmark"]

    # Define portfolio sector allocation
    # Aggregate sector value for stocks and crypto
@@ -99,11 +141,9 @@ def get_sector_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):
        .groupby(by="Sector")
        .agg({"Portfolio Value": "sum"})
    )
-    p_bar.n += 1
-    p_bar.refresh()

    # Aggregate sector value for ETFs
-    # Start by getting value by isin/ticker
+    # Start by getting value by isin/symbol
    etf_ticker_value = (
        portfolio_trades[portfolio_trades["Type"].isin(["ETF"])]
        .groupby(by="Ticker")
@@ -111,48 +151,45 @@ def get_sector_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):
    )
    etf_global_sector_alloc = pd.DataFrame()

-    # Loop through each etf and multiply sector weights by current value
-    for item in etf_ticker_value.index.values:
+    if not etf_ticker_value.empty:
+        # Loop through each etf and multiply sector weights by current value
+        for item in tqdm(etf_ticker_value.index.values, desc="Loading ETF data"):

-        # TODO: This can be improved by caching this info similar to what is done in stocks
-        etf_info = yf.Ticker(item).info
+            # TODO: This can be improved by caching this info similar to what is done in stocks
+            etf_info = yf.Ticker(item).info

-        try:
-            etf_sector_weight = pd.DataFrame.from_dict(
-                data={
-                    sector_name: allocation
-                    for sector in etf_info["sectorWeightings"]
-                    for sector_name, allocation in sector.items()
-                },
-                orient="index",
-                columns=["Portfolio Value"],
+            try:
+                etf_sector_weight = pd.DataFrame.from_dict(
+                    data={
+                        sector_name: allocation
+                        for sector in etf_info["sectorWeightings"]
+                        for sector_name, allocation in sector.items()
+                    },
+                    orient="index",
+                    columns=["Portfolio Value"],
+                )
+
+            except Exception:
+                # If ETF has no sectors like VIX for example or it was not found, add to Other
+                etf_sector_weight = pd.DataFrame.from_dict(
+                    data={"Other": 1}, orient="index", columns=["Portfolio Value"]
+                )
+
+            etf_ticker_sector_alloc = (
+                etf_sector_weight * etf_ticker_value["Portfolio Value"][item]
            )

-        except Exception:
-            # If ETF has no sectors like VIX for example or it was not found, add to Other
-            etf_sector_weight = pd.DataFrame.from_dict(
-                data={"Other": 1}, orient="index", columns=["Portfolio Value"]
+            # Aggregate etf sector allocation by value
+            etf_global_sector_alloc = pd.concat(
+                [etf_global_sector_alloc, etf_ticker_sector_alloc], axis=1
            )
+            etf_global_sector_alloc.fillna(0, inplace=True)
+            etf_global_sector_alloc = etf_global_sector_alloc.sum(axis=1)

-        etf_value = etf_ticker_value["Portfolio Value"][item]
-
-        etf_ticker_sector_alloc = etf_sector_weight * etf_value
-
-        # Aggregate etf sector allocation by value
-        etf_global_sector_alloc = pd.concat(
-            [etf_global_sector_alloc, etf_ticker_sector_alloc], axis=1
+        etf_global_sector_alloc = pd.DataFrame(
+            etf_global_sector_alloc, columns=["Portfolio Value"]
        )
-
-        etf_global_sector_alloc.fillna(0, inplace=True)
-
-        etf_global_sector_alloc = etf_global_sector_alloc.sum(axis=1)
-
-    p_bar.n += 1
-    p_bar.refresh()
-
-    etf_global_sector_alloc = pd.DataFrame(
-        etf_global_sector_alloc, columns=["Portfolio Value"]
-    )
+        console.print("\n")

    # Rename columns to match stock and crypto classification
    etf_global_sector_alloc.index.name = "Sector"
@@ -175,51 +212,101 @@ def get_sector_allocation(benchmark_info: Dict, portfolio_trades: pd.DataFrame):
        portfolio_sectors_allocation, columns=["Portfolio Value"]
    )

-    portfolio_sectors_allocation = (
-        portfolio_sectors_allocation.div(portfolio_trades["Portfolio Value"].sum())
-        .squeeze(axis=1)
-        .sort_values(ascending=False)
-    )
+    portfolio_sectors_allocation = portfolio_sectors_allocation.div(
+        portfolio_trades["Portfolio Value"].sum()
+    ).sort_values(by="Portfolio Value", ascending=False)

    portfolio_sectors_allocation.fillna(0, inplace=True)
-
-    p_bar.n += 1
-    p_bar.refresh()
-    p_bar.disable = True
-    console.print("\n")
+    portfolio_sectors_allocation = pd.DataFrame(portfolio_sectors_allocation)
+    portfolio_sectors_allocation.reset_index(inplace=True)
+    portfolio_sectors_allocation.columns = ["Sector", "Portfolio"]

    return benchmark_sectors_allocation, portfolio_sectors_allocation


@log_start_end(log=logger)
-def get_region_country_allocation(
-    ticker: str, region_test: list = None, country_test: list = None
-):
-
-    """Obtain the region and country allocation for ETF ticker. [Source: Fidelity.com]
+def get_countries_allocation(
+    benchmark_info: Dict, portfolio_trades: pd.DataFrame
+) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    """Get countries allocation for benchmark and portfolio [Source: Yahoo Finance]

    Parameters
    ----------
-    benchmark_ticker: str
-        The ticker, e.g. "SPY"
-    region_test: list
-        This includes a list of region names that should be used to discover
-        which list on the Fidelity page is the correct one
-    country_test: list
-        This includes a list of country names that should be used to discover
-        which list on the Fidelity page is the correct one
+    benchmark_info: Dict
+        Dictionary containing Yahoo Finance information
+    portfolio_trades: pd.DataFrame
+        Object containing trades made within the portfolio

    Returns
    -------
-    region_allocation: dict
-        Dictionary with regional allocations.
-    country_allocation: dict
+    pd.DataFrame
+        DataFrame with regional allocations.
+    pd.DataFrame
+        DataFrame with country allocations
+    """
+
+    benchmark_allocation = get_symbol_allocation(
+        symbol=benchmark_info["symbol"], category="Country", col_name="Benchmark"
+    )
+
+    portfolio_allocation = get_portfolio_allocation(
+        category="Country", portfolio_trades=portfolio_trades
+    )
+
+    return benchmark_allocation, portfolio_allocation
+
+
+@log_start_end(log=logger)
+def get_regions_allocation(
+    benchmark_info: Dict, portfolio_trades: pd.DataFrame
+) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    """Get regions allocation for benchmark and portfolio [Source: Yahoo Finance]
+
+    Parameters
+    ----------
+    benchmark_info: Dict
+        Dictionary containing Yahoo Finance information
+    portfolio_trades: pd.DataFrame
+        Object containing trades made within the portfolio
+
+    Returns
+    -------
+    pd.DataFrame
+        DataFrame with regional allocations.
+    pd.DataFrame
+        DataFrame with country allocations
+    """
+    benchmark_allocation = get_symbol_allocation(
+        symbol=benchmark_info["symbol"], category="Region", col_name="Benchmark"
+    )
+
+    portfolio_allocation = get_portfolio_allocation(
+        category="Region", portfolio_trades=portfolio_trades
+    )
+
+    return benchmark_allocation, portfolio_allocation
+
+
+def get_symbol_allocation(
+    symbol: str, category: str, col_name: str = "Weight"
+) -> pd.DataFrame:
+    """Get benchmark allocation [Source: Fidelity]
+
+    Parameters
+    ----------
+    symbol: str
+        ETF symbol to get allocation
+    category: str
+        Chosen category: Country or Region
+
+    Returns
+    -------
+    pd.DataFrame
        Dictionary with country allocations
    """

-    # Initialize variables
-    if not region_test:
-        region_test = [
+    if category == "Region":
+        category_list = [
            "North America",
            "Europe",
            "Asia",
@@ -227,8 +314,9 @@ def get_region_country_allocation(
            "Africa",
            "Middle East",
        ]
-    if not country_test:
-        country_test = [
+
+    if category == "Country":
+        category_list = [
            "United States",
            "United Kingdom",
            "Japan",
@@ -236,189 +324,129 @@ def get_region_country_allocation(
            "China",
        ]

-    region_list = 0
-    country_list = 0
+    item_list = 0

    # Collect data from Fidelity about the portfolio composition of the benchmark
-    URL = f"https://screener.fidelity.com/ftgw/etf/goto/snapshot/portfolioComposition.jhtml?symbols={ticker}"
+    URL = f"https://screener.fidelity.com/ftgw/etf/goto/snapshot/portfolioComposition.jhtml?symbols={symbol}"
    html = requests.get(URL).content
    df_list = pd.read_html(html)

    # Find the ones that contain regions and countries
    for index, item in enumerate(df_list):
-        for region in region_test:
-            if region in item.values:
-                region_list = index
-                break
-        for country in country_test:
-            if country in item.values:
-                country_list = index
+        for category_item in category_list:
+            if category_item in item.values:
+                item_list = index
                break

-    if region_list:
-        region_allocation = {
+    if item_list:
+        allocation = {
            row[1]: float(row[2].strip("%")) / 100
-            for _, row in df_list[region_list].dropna(axis="columns").iterrows()
+            for _, row in df_list[item_list].dropna(axis="columns").iterrows()
        }
-        region_allocation = pd.DataFrame.from_dict(
-            region_allocation, orient="index"
-        ).squeeze()
+        allocation_df = pd.DataFrame.from_dict(allocation, orient="index")
+        allocation_df.reset_index(inplace=True)
+        allocation_df.columns = [category, col_name]
    else:
-        region_allocation = pd.DataFrame()
+        allocation_df = pd.DataFrame(columns=[category, col_name])

-    if country_list:
-        country_allocation = {
-            row[1]: float(row[2].strip("%")) / 100
-            for _, row in df_list[country_list].dropna(axis="columns").iterrows()
-        }
-        country_allocation = pd.DataFrame.from_dict(
-            country_allocation, orient="index"
-        ).squeeze()
-    else:
-        country_allocation = pd.DataFrame()
-
-    return region_allocation, country_allocation
+    return allocation_df


@log_start_end(log=logger)
-def get_portfolio_region_country_allocation(portfolio_trades: pd.DataFrame):
-    """Obtain the regional and country allocation of the portfolio.
+def get_portfolio_allocation(
+    category: str, portfolio_trades: pd.DataFrame
+) -> pd.DataFrame:
+    """Get portfolio allocation

    Parameters
    ----------
+    category: str
+        Chosen category: Country or Region
    portfolio_trades: pd.DataFrame
-        Object containing trades made within the portfolio.
+        Object containing trades made within the portfolio

    Returns
-    ------
-    portfolio_regional_allocation: pd.DataFrame
-        Dictionary with regional allocations.
-    portfolio_country_allocation: pd.DataFrame
+    -------
+    pd.DataFrame
        Dictionary with country allocations
    """

-    p_bar = tqdm(range(3), desc="Loading country/region data")
-
-    # Define portfolio regional allocation
-    if not portfolio_trades["Region"].isnull().any():
-        portfolio_region_allocation = (
+    # Define portfolio allocation
+    if not portfolio_trades[category].isnull().any():
+        allocation = (
            portfolio_trades[portfolio_trades["Type"].isin(["STOCK", "CRYPTO"])]
-            .groupby(by="Region")
+            .groupby(by=category)
            .agg({"Portfolio Value": "sum"})
        )
    else:
-        portfolio_region_allocation = pd.DataFrame()
-
-    # Define portfolio country allocation
-    if not portfolio_trades["Country"].isnull().any():
-        portfolio_country_allocation = (
-            portfolio_trades[portfolio_trades["Type"].isin(["STOCK", "CRYPTO"])]
-            .groupby(by="Country")
-            .agg({"Portfolio Value": "sum"})
-        )
-    else:
-        portfolio_country_allocation = pd.DataFrame()
-
-    p_bar.n += 1
-    p_bar.refresh()
+        allocation = pd.DataFrame()

    # Aggregate sector value for ETFs
-    # Start by getting value by ticker
+    # Start by getting value by symbol
    etf_ticker_value = (
        portfolio_trades[portfolio_trades["Type"].isin(["ETF"])]
        .groupby(by="Ticker")
        .agg({"Portfolio Value": "sum"})
    )
-    etf_global_region_alloc = pd.DataFrame()
-    etf_global_country_alloc = pd.DataFrame()
+    etf_global_alloc = pd.DataFrame(columns=[category, "Portfolio Value"])

-    # Loop through each etf and multiply sector weights by current value
-    for item in etf_ticker_value.index.values:
+    if not etf_ticker_value.empty:

-        etf_region_weight, etf_country_weight = get_region_country_allocation(item)
+        no_info = []
+        # Loop through each etf and multiply sector weights by current value
+        for item in tqdm(etf_ticker_value.index.values, desc="Loading ETF data"):

-        if etf_region_weight.empty:
-            # If ETF has no sectors like VIX for example or it was not found, add to Other
-            etf_region_weight = pd.DataFrame.from_dict(
-                data={"Other": 1}, orient="index", columns=["Portfolio Value"]
+            etf_weight = get_symbol_allocation(
+                symbol=item, category=category, col_name="Portfolio Value"
            )

-        if etf_country_weight.empty:
-            etf_country_weight = pd.DataFrame.from_dict(
-                data={"Other": 1}, orient="index", columns=["Portfolio Value"]
+            if etf_weight.empty:
+                etf_weight = pd.DataFrame.from_dict(
+                    data={"Other": 1}, orient="index", columns=["Portfolio Value"]
+                )
+                etf_weight.index.name = category
+                no_info.append(item)
+            else:
+                etf_weight.set_index(category, inplace=True)
+
+            # Aggregate etf allocation by value
+            etf_ticker_alloc = etf_weight
+            etf_ticker_alloc["Portfolio Value"] = (
+                etf_ticker_alloc["Portfolio Value"]
+                * etf_ticker_value["Portfolio Value"][item]
+            )
+            etf_global_alloc = pd.concat([etf_global_alloc, etf_ticker_alloc], axis=1)
+            etf_global_alloc.fillna(0, inplace=True)
+            etf_global_alloc = etf_global_alloc.sum(axis=1)
+
+        etf_global_alloc = pd.DataFrame(etf_global_alloc, columns=["Portfolio Value"])
+
+        console.print("")
+
+        if no_info:
+            console.print(
+                f"[red]No data found for: {', '.join(no_info)}. Included in 'Other'.[/red]\n"
            )

-        etf_value = etf_ticker_value["Portfolio Value"][item]
-
-        # Aggregate etf region allocation by value
-        etf_ticker_region_alloc = etf_region_weight * etf_value
-        etf_global_region_alloc = pd.concat(
-            [etf_global_region_alloc, etf_ticker_region_alloc], axis=1
-        )
-        etf_global_region_alloc.fillna(0, inplace=True)
-        etf_global_region_alloc = etf_global_region_alloc.sum(axis=1)
-
-        # Aggregate etf country allocation by value
-        etf_ticker_country_alloc = etf_country_weight * etf_value
-        etf_global_country_alloc = pd.concat(
-            [etf_global_country_alloc, etf_ticker_country_alloc], axis=1
-        )
-        etf_global_country_alloc.fillna(0, inplace=True)
-        etf_global_country_alloc = etf_global_country_alloc.sum(axis=1)
-
-    p_bar.n += 1
-    p_bar.refresh()
-
-    etf_global_region_alloc = pd.DataFrame(
-        etf_global_region_alloc, columns=["Portfolio Value"]
-    )
-    etf_global_country_alloc = pd.DataFrame(
-        etf_global_country_alloc, columns=["Portfolio Value"]
-    )
-
-    # Aggregate region allocation for stocks and crypto with ETFs
-    portfolio_region_allocation = pd.merge(
-        portfolio_region_allocation,
-        etf_global_region_alloc,
+    # Aggregate allocation for stocks and crypto with ETFs
+    allocation = pd.merge(
+        allocation,
+        etf_global_alloc,
        how="outer",
        left_index=True,
        right_index=True,
    ).sum(axis=1)

-    # Aggregate country allocation for stocks and crypto with ETFs
-    portfolio_country_allocation = pd.merge(
-        portfolio_country_allocation,
-        etf_global_country_alloc,
-        how="outer",
-        left_index=True,
-        right_index=True,
-    ).sum(axis=1)
+    allocation = pd.DataFrame(allocation, columns=["Portfolio Value"])

-    portfolio_region_allocation = pd.DataFrame(
-        portfolio_region_allocation, columns=["Portfolio Value"]
-    )
-    portfolio_country_allocation = pd.DataFrame(
-        portfolio_country_allocation, columns=["Portfolio Value"]
+    allocation = allocation.div(portfolio_trades["Portfolio Value"].sum()).sort_values(
+        by="Portfolio Value", ascending=False
    )

-    portfolio_region_allocation = (
-        portfolio_region_allocation.div(portfolio_trades["Portfolio Value"].sum())
-        .squeeze(axis=1)
-        .sort_values(ascending=False)
-    )
+    allocation.fillna(0, inplace=True)

-    portfolio_country_allocation = (
-        portfolio_country_allocation.div(portfolio_trades["Portfolio Value"].sum())
-        .squeeze(axis=1)
-        .sort_values(ascending=False)
-    )
+    allocation.reset_index(inplace=True)

-    portfolio_region_allocation.fillna(0, inplace=True)
-    portfolio_country_allocation.fillna(0, inplace=True)
+    allocation.columns = [category, "Portfolio"]

-    p_bar.n += 1
-    p_bar.refresh()
-    p_bar.disable = True
-    console.print("\n")
-
-    return portfolio_region_allocation, portfolio_country_allocation
+    return allocation
--- a/openbb_terminal/portfolio/portfolio_controller.py
+++ b/openbb_terminal/portfolio/portfolio_controller.py
@@ -22,7 +22,7 @@ from openbb_terminal.helper_funcs import (
 from openbb_terminal.menu import session
 from openbb_terminal.core.config.paths import MISCELLANEOUS_DIRECTORY
 from openbb_terminal.parent_classes import BaseController
-from openbb_terminal.portfolio import portfolio_model
+from openbb_terminal.portfolio.portfolio_model import generate_portfolio
 from openbb_terminal.portfolio import statics
 from openbb_terminal.portfolio import portfolio_view
 from openbb_terminal.portfolio import portfolio_helper
@@ -139,9 +139,7 @@ class PortfolioController(BaseController):
        self.original_benchmark_name = ""
        self.risk_free_rate = 0
        self.portlist: List[str] = os.listdir(self.DEFAULT_HOLDINGS_PATH)
-        self.portfolio: portfolio_model.PortfolioModel = (
-            portfolio_model.PortfolioModel()
-        )
+        self.portfolio = None

        if session and obbff.USE_PROMPT_TOOLKIT:
            self.update_choices()
@@ -442,33 +440,26 @@ class PortfolioController(BaseController):
            else:
                file_location = ns_parser.file  # type: ignore

-            transactions = portfolio_model.PortfolioModel.read_transactions(
-                str(file_location)
+            self.portfolio = generate_portfolio(
+                transactions_file_path=str(file_location),
+                benchmark_symbol="SPY",
+                risk_free_rate=ns_parser.risk_free_rate / 100,
            )
-            self.portfolio = portfolio_model.PortfolioModel(transactions)
-            self.benchmark_name = ""

            if ns_parser.name:
                self.portfolio_name = ns_parser.name
            else:
                self.portfolio_name = ns_parser.file
-
-            # Generate holdings from trades
-            self.portfolio.generate_portfolio_data()
-
-            # Add in the Risk-free rate
-            self.portfolio.set_risk_free_rate(ns_parser.risk_free_rate / 100)
-            self.risk_free_rate = ns_parser.risk_free_rate / 100
-
-            # Load benchmark
-            self.call_bench(["-b", "SPDR S&P 500 ETF Trust (SPY)"])
-
            console.print(
                f"\n[bold][param]Portfolio:[/param][/bold] {self.portfolio_name}"
            )
+
+            self.benchmark_name = "SPDR S&P 500 ETF Trust (SPY)"
            console.print(
                f"[bold][param]Risk Free Rate:[/param][/bold] {self.risk_free_rate:.2%}"
            )
+
+            self.risk_free_rate = ns_parser.risk_free_rate / 100
            console.print(
                f"[bold][param]Benchmark:[/param][/bold] {self.benchmark_name}\n"
            )
@@ -538,19 +529,10 @@ class PortfolioController(BaseController):
                else:
                    benchmark_ticker = chosen_benchmark

-                self.portfolio.load_benchmark(benchmark_ticker, ns_parser.full_shares)
+                self.portfolio.set_benchmark(benchmark_ticker, ns_parser.full_shares)

                self.benchmark_name = chosen_benchmark

-                # Make it so that there is no chance of there being a difference in length between
-                # the portfolio and benchmark return DataFrames
-                (
-                    self.portfolio.returns,
-                    self.portfolio.benchmark_returns,
-                ) = portfolio_helper.make_equal_length(
-                    self.portfolio.returns, self.portfolio.benchmark_returns
-                )
-
            else:
                console.print(
                    "[red]Please first load transactions file using 'load'[/red]\n"
@@ -596,41 +578,26 @@ class PortfolioController(BaseController):
                self.portfolio_name, self.benchmark_name
            ):
                if ns_parser.agg == "assets":
-                    if self.portfolio.portfolio_assets_allocation.empty:
-                        self.portfolio.calculate_allocations("asset")
                    portfolio_view.display_assets_allocation(
-                        self.portfolio.portfolio_assets_allocation,
-                        self.portfolio.benchmark_assets_allocation,
+                        self.portfolio,
                        ns_parser.limit,
                        ns_parser.tables,
                    )
                elif ns_parser.agg == "sectors":
-                    if self.portfolio.portfolio_sectors_allocation.empty:
-                        self.portfolio.calculate_allocations("sector")
-                    portfolio_view.display_category_allocation(
-                        self.portfolio.portfolio_sectors_allocation,
-                        self.portfolio.benchmark_sectors_allocation,
-                        ns_parser.agg,
+                    portfolio_view.display_sectors_allocation(
+                        self.portfolio,
                        ns_parser.limit,
                        ns_parser.tables,
                    )
                elif ns_parser.agg == "countries":
-                    if self.portfolio.portfolio_country_allocation.empty:
-                        self.portfolio.calculate_allocations("country")
-                    portfolio_view.display_category_allocation(
-                        self.portfolio.portfolio_country_allocation,
-                        self.portfolio.benchmark_country_allocation,
-                        ns_parser.agg,
+                    portfolio_view.display_countries_allocation(
+                        self.portfolio,
                        ns_parser.limit,
                        ns_parser.tables,
                    )
                elif ns_parser.agg == "regions":
-                    if self.portfolio.portfolio_region_allocation.empty:
-                        self.portfolio.calculate_allocations("region")
-                    portfolio_view.display_category_allocation(
-                        self.portfolio.portfolio_region_allocation,
-                        self.portfolio.benchmark_region_allocation,
-                        ns_parser.agg,
+                    portfolio_view.display_regions_allocation(
+                        self.portfolio,
                        ns_parser.limit,
                        ns_parser.tables,
                    )
@@ -909,7 +876,7 @@ class PortfolioController(BaseController):
                    )
                else:
                    portfolio_view.display_var(
-                        portfolio=self.portfolio,
+                        portfolio_engine=self.portfolio,
                        use_mean=ns_parser.use_mean,
                        adjusted_var=ns_parser.adjusted,
                        student_t=ns_parser.student_t,
@@ -966,7 +933,7 @@ class PortfolioController(BaseController):
        if ns_parser and self.portfolio is not None:
            if self.portfolio_name:
                portfolio_view.display_es(
-                    portfolio=self.portfolio,
+                    portfolio_engine=self.portfolio,
                    use_mean=ns_parser.use_mean,
                    distribution=ns_parser.distribution,
                    percentile=ns_parser.percentile,
@@ -1277,7 +1244,7 @@ class PortfolioController(BaseController):
                self.portfolio_name, self.benchmark_name
            ):
                portfolio_view.display_rolling_sortino(
-                    portfolio=self.portfolio,
+                    portfolio_engine=self.portfolio,
                    risk_free_rate=ns_parser.risk_free_rate / 100,
                    window=ns_parser.period,
                    export=ns_parser.export,
--- a/openbb_terminal/portfolio/portfolio_helper.py
+++ b/openbb_terminal/portfolio/portfolio_helper.py
@@ -1046,7 +1046,7 @@ def get_kelly_criterion(
        if (not period_return.empty) and (not period_portfolio_tr.empty):
            w = len(period_return[period_return > 0]) / len(period_return)
            r = len(
-                period_portfolio_tr[period_portfolio_tr["% Portfolio Return"] > 0]
+                period_portfolio_tr[period_portfolio_tr["Portfolio % Return"] > 0]
            ) / len(
                period_portfolio_tr[period_portfolio_tr["Type"].str.upper() != "CASH"]
            )
@@ -1086,10 +1086,10 @@ def get_payoff_ratio(portfolio_trades: pd.DataFrame) -> pd.DataFrame:
        period_portfolio_tr = filter_df_by_period(portfolio_trades, period)
        if not portfolio_trades.empty:
            portfolio_wins = period_portfolio_tr[
-                period_portfolio_tr["% Portfolio Return"] > 0
+                period_portfolio_tr["Portfolio % Return"] > 0
            ]
            portfolio_loses = period_portfolio_tr[
-                period_portfolio_tr["% Portfolio Return"] < 0
+                period_portfolio_tr["Portfolio % Return"] < 0
            ]
            if portfolio_loses.empty:
                vals.append(["-"])
@@ -1140,10 +1140,10 @@ def get_profit_factor(portfolio_trades: pd.DataFrame) -> pd.DataFrame:
        period_portfolio_tr = filter_df_by_period(portfolio_trades, period)
        if not portfolio_trades.empty:
            portfolio_wins = period_portfolio_tr[
-                period_portfolio_tr["% Portfolio Return"] > 0
+                period_portfolio_tr["Portfolio % Return"] > 0
            ]
            portfolio_loses = period_portfolio_tr[
-                period_portfolio_tr["% Portfolio Return"] < 0
+                period_portfolio_tr["Portfolio % Return"] < 0
            ]
            if portfolio_loses.empty:
                vals.append(["-"])
--- a/openbb_terminal/portfolio/portfolio_model.py
+++ b/openbb_terminal/portfolio/portfolio_model.py
--- a/openbb_terminal/portfolio/portfolio_view.py
+++ b/openbb_terminal/portfolio/portfolio_view.py
--- a/openbb_terminal/reports/templates/portfolio.ipynb
+++ b/openbb_terminal/reports/templates/portfolio.ipynb
@@ -35,8 +35,7 @@
    "\n",
    "from openbb_terminal.reports import widget_helpers as widgets\n",
    "from openbb_terminal.sdk import openbb\n",
-    "from openbb_terminal.sdk import openbb import helper\n",
-    "from openbb_terminal.sdk import openbb import Portfolio\n",
+    "from openbb_terminal.sdk import helper\n",
    "from openbb_terminal.helper_classes import TerminalStyle\n",
    "from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
    "\n",
@@ -90,7 +89,7 @@
   "source": [
    "# Parameters that will be replaced when calling this notebook\n",
    "# Do not leave parameters blank as notebook will not run otherwise\n",
-    "transactions = \"Public_Equity_Orderbook.xlsx\"\n",
+    "transactions = \"market.csv\"\n",
    "report_name = \"Portfolio Report\""
   ]
  },
@@ -138,11 +137,8 @@
   "outputs": [],
   "source": [
    "try:\n",
-    "    transactions = Portfolio.read_transactions(transactions_path)\n",
-    "    P = Portfolio(transactions)\n",
-    "    P.generate_portfolio_data()\n",
-    "    P.load_benchmark()\n",
-    "    P.get_transactions()\n",
+    "    P = openbb.portfolio.load(transactions_path)\n",
+    "    openbb.portfolio.show(P)\n",
    "except ValueError:\n",
    "    raise ValueError(\n",
    "        \"Failed to load the transactions. Is this file inside the 'holdings' folder?\"\n",
@@ -205,7 +201,7 @@
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(11, 5), dpi=150)\n",
-    "openbb.portfolio.rsortino(P, chart=True, external_axes=[ax])\n",
+    "openbb.portfolio.rsort(P, chart=True, external_axes=[ax])\n",
    "\n",
    "fig.tight_layout()\n",
    "f = io.BytesIO()\n",
@@ -236,19 +232,17 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "P.calculate_allocations(\"country\")\n",
+    "country_allocation = openbb.portfolio.alloc.countries(P)\n",
    "\n",
-    "country_allocation = pd.DataFrame(\n",
-    "    [P.portfolio_country_allocation, P.benchmark_country_allocation]\n",
-    ").T\n",
-    "country_allocation.columns = [\"Portfolio\", \"Benchmark\"]\n",
-    "country_allocation.fillna(\"-\", inplace=True)\n",
    "country_allocation[\"Portfolio\"] = (country_allocation[\"Portfolio\"] * 100).map(\n",
    "    \"{:.3}%\".format\n",
    ")\n",
    "country_allocation[\"Benchmark\"] = (country_allocation[\"Benchmark\"] * 100).map(\n",
    "    \"{:.3}%\".format\n",
    ")\n",
+    "country_allocation[\"Difference\"] = (country_allocation[\"Difference\"] * 100).map(\n",
+    "    \"{:.3}pp\".format\n",
+    ")\n",
    "\n",
    "country_allocation"
   ]
@@ -260,19 +254,17 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "P.calculate_allocations(\"sector\")\n",
+    "sector_allocation = openbb.portfolio.alloc.sectors(P)\n",
    "\n",
-    "sector_allocation = pd.DataFrame(\n",
-    "    [P.portfolio_sectors_allocation, P.benchmark_sectors_allocation]\n",
-    ").T\n",
-    "sector_allocation.columns = [\"Portfolio\", \"Benchmark\"]\n",
-    "sector_allocation.fillna(\"-\", inplace=True)\n",
    "sector_allocation[\"Portfolio\"] = (sector_allocation[\"Portfolio\"] * 100).map(\n",
    "    \"{:.3}%\".format\n",
    ")\n",
    "sector_allocation[\"Benchmark\"] = (sector_allocation[\"Benchmark\"] * 100).map(\n",
    "    \"{:.3}%\".format\n",
    ")\n",
+    "sector_allocation[\"Difference\"] = (sector_allocation[\"Difference\"] * 100).map(\n",
+    "    \"{:.3}pp\".format\n",
+    ")\n",
    "\n",
    "sector_allocation"
   ]
@@ -413,24 +405,24 @@
    ")\n",
    "\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Tracking Error\") + openbb.portfolio.trackerr(P)[0].to_html()]\n",
+    "    [widgets.h(3, \"Tracking Error\") + openbb.portfolio.metric.trackerr(P)[0].to_html()]\n",
    ")\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Information Ratio\") + openbb.portfolio.information(P).to_html()]\n",
+    "    [widgets.h(3, \"Information Ratio\") + openbb.portfolio.metric.information(P).to_html()]\n",
    ")\n",
    "\n",
    "htmlcode += widgets.row([widgets.h(3, \"Beta Chart\") + beta_chart])\n",
    "\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Sharpe Ratio\") + openbb.portfolio.sharpe(P).to_html()]\n",
+    "    [widgets.h(3, \"Sharpe Ratio\") + openbb.portfolio.metric.sharpe(P).to_html()]\n",
    ")\n",
    "htmlcode += widgets.row([widgets.h(3, \"Sharpe Ratio Chart\") + sharpe_chart])\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Volatility\") + openbb.portfolio.volatility(P).to_html()]\n",
+    "    [widgets.h(3, \"Volatility\") + openbb.portfolio.metric.volatility(P).to_html()]\n",
    ")\n",
    "htmlcode += widgets.row([widgets.h(3, \"Volatility Chart\") + volatility_chart])\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Sortino Ratio\") + openbb.portfolio.sortino(P).to_html()]\n",
+    "    [widgets.h(3, \"Sortino Ratio\") + openbb.portfolio.metric.sortino(P).to_html()]\n",
    ")\n",
    "htmlcode += widgets.row([widgets.h(3, \"Sortino Chart\") + sortino_chart])\n",
    "\n",
@@ -443,12 +435,12 @@
    "htmlcode = widgets.row([widgets.h(3, \"Distribution\") + distr_chart])\n",
    "htmlcode += widgets.row([widgets.h(3, \"Daily Returns\") + dret_chart])\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Volatility\") + openbb.portfolio.volatility(P).to_html()]\n",
+    "    [widgets.h(3, \"Volatility\") + openbb.portfolio.metric.volatility(P).to_html()]\n",
    ")\n",
    "htmlcode += widgets.row(\n",
-    "    [widgets.h(3, \"Kurtosis\") + openbb.portfolio.kurtosis(P).to_html()]\n",
+    "    [widgets.h(3, \"Kurtosis\") + openbb.portfolio.metric.kurtosis(P).to_html()]\n",
    ")\n",
-    "htmlcode += widgets.row([widgets.h(3, \"Skew\") + openbb.portfolio.skew(P).to_html()])\n",
+    "htmlcode += widgets.row([widgets.h(3, \"Skew\") + openbb.portfolio.metric.skew(P).to_html()])\n",
    "htmlcode += widgets.row(\n",
    "    [widgets.h(3, \"Value at Risk (VaR)\") + openbb.portfolio.var(P).to_html()]\n",
    ")\n",
@@ -474,7 +466,7 @@
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
-   "display_name": "Python 3.10.4 ('obb')",
+   "display_name": "Python 3.9.13 ('obb')",
   "language": "python",
   "name": "python3"
  },
@@ -488,11 +480,11 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.9.13"
  },
  "vscode": {
   "interpreter": {
-    "hash": "1a8cc6b6e60740679b24fc1ea93bdeb94d949a22102a80c99b7fd3f0d572afd6"
+    "hash": "e784374cc4f9a84ed6af2983247aaf351b155c82bcc2188134a65f3c99031000"
   }
  }
 },
--- a/openbb_terminal/sdk.py
+++ b/openbb_terminal/sdk.py
@@ -3,9 +3,6 @@ from openbb_terminal.config_terminal import theme  # noqa: F401
 from openbb_terminal.helper_classes import TerminalStyle
 from openbb_terminal import helper_funcs as helper  # noqa: F401
 from openbb_terminal.reports import widget_helpers as widgets  # noqa: F401
-from openbb_terminal.portfolio.portfolio_model import (  # noqa: F401
-    PortfolioModel as Portfolio,
-)
 from openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model import (  # noqa: F401
    Coin,
 )
--- a/website/content/SDK/crypto/dd/active/_index.rst
+++ b/website/content/SDK/crypto/dd/active/_index.rst
@@ -17,7 +17,7 @@ crypto.dd.active(
    symbol: str,
    interval: str = '24h',
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -60,7 +60,7 @@ crypto.dd.active(
 crypto.dd.active(
    symbol: str,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    interval: str = '24h',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/crypto/dd/change/_index.rst
+++ b/website/content/SDK/crypto/dd/change/_index.rst
@@ -17,7 +17,7 @@ crypto.dd.change(
    symbol: str,
    exchange: str = 'binance',
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -61,7 +61,7 @@ crypto.dd.change(
    symbol: str,
    exchange: str = 'binance',
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/crypto/dd/close/_index.rst
+++ b/website/content/SDK/crypto/dd/close/_index.rst
@@ -14,7 +14,7 @@
 crypto.dd.close(
    symbol: str,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    print_errors: bool = True,
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
--- a/website/content/SDK/crypto/dd/eb/_index.rst
+++ b/website/content/SDK/crypto/dd/eb/_index.rst
@@ -17,7 +17,7 @@ crypto.dd.eb(
    symbol: str,
    exchange: str = 'binance',
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -61,7 +61,7 @@ crypto.dd.eb(
    symbol: str,
    exchange: str = 'binance',
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    percentage: bool = False,
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/crypto/dd/gh/_index.rst
+++ b/website/content/SDK/crypto/dd/gh/_index.rst
@@ -17,8 +17,8 @@ crypto.dd.gh(
    symbol: str,
    dev_activity: bool = False,
    interval: str = '1d',
-    start_date: str = '2021-11-10T20:12:25Z',
-    end_date: str = '2022-11-10T20:12:25Z',
+    start_date: str = '2021-11-14T14:32:50Z',
+    end_date: str = '2022-11-14T14:32:50Z',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -63,9 +63,9 @@ crypto.dd.gh(
 {{< highlight python >}}
 crypto.dd.gh(
    symbol: str,
-    start_date: str = '2021-11-10T20:12:25Z',
+    start_date: str = '2021-11-14T14:32:50Z',
    dev_activity: bool = False,
-    end_date: str = '2022-11-10T20:12:25Z',
+    end_date: str = '2022-11-14T14:32:50Z',
    interval: str = '1d',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/crypto/dd/mcapdom/_index.rst
+++ b/website/content/SDK/crypto/dd/mcapdom/_index.rst
@@ -16,8 +16,8 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 crypto.dd.mcapdom(
    symbol: str,
    interval: str = '1d',
-    start_date: str = '2021-11-10',
-    end_date: str = '2022-11-10',
+    start_date: str = '2021-11-14',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -59,8 +59,8 @@ crypto.dd.mcapdom(
 {{< highlight python >}}
 crypto.dd.mcapdom(
    symbol: str,
-    start_date: str = '2021-11-10',
-    end_date: str = '2022-11-10',
+    start_date: str = '2021-11-14',
+    end_date: str = '2022-11-14',
    interval: str = '1d',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/crypto/dd/mt/_index.rst
+++ b/website/content/SDK/crypto/dd/mt/_index.rst
@@ -17,8 +17,8 @@ crypto.dd.mt(
    symbol: str,
    timeseries_id: str,
    interval: str = '1d',
-    start_date: str = '2021-11-10',
-    end_date: str = '2022-11-10',
+    start_date: str = '2021-11-14',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> Tuple[pandas.core.frame.DataFrame, str]
 {{< /highlight >}}
@@ -65,8 +65,8 @@ crypto.dd.mt(
 crypto.dd.mt(
    symbol: str,
    timeseries_id: str,
-    start_date: str = '2021-11-10',
-    end_date: str = '2022-11-10',
+    start_date: str = '2021-11-14',
+    end_date: str = '2022-11-14',
    interval: str = '1d',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/crypto/dd/nonzero/_index.rst
+++ b/website/content/SDK/crypto/dd/nonzero/_index.rst
@@ -16,7 +16,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 crypto.dd.nonzero(
    symbol: str,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -57,7 +57,7 @@ crypto.dd.nonzero(
 crypto.dd.nonzero(
    symbol: str,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/crypto/dd/oi/_index.rst
+++ b/website/content/SDK/crypto/dd/oi/_index.rst
@@ -73,7 +73,7 @@ crypto.dd.oi(
    interval : int
        Frequency (possible values are: 0 for ALL, 2 for 1H, 1 for 4H, 4 for 12H), by default 0
    export : str
-        Export dataframe data to csv,json,xlsx fil
+        Export dataframe data to csv,json,xlsx file
    chart: bool
       Flag to display chart

--- a/website/content/SDK/crypto/load/_index.rst
+++ b/website/content/SDK/crypto/load/_index.rst
@@ -13,12 +13,10 @@
 {{< highlight python >}}
 crypto.load(
    symbol: 'str',
-    start_date: 'Optional[Union[datetime, str]]' = None,
-    interval: 'str' = '1440',
+    start_date: 'datetime | str | None' = None, interval: 'str' = '1440',
    exchange: 'str' = 'binance',
    vs_currency: 'str' = 'usdt',
-    end_date: 'Optional[Union[datetime, str]]' = None,
-    source: 'str' = 'CCXT',
+    end_date: 'datetime | str | None' = None, source: 'str' = 'CCXT',
    chart: bool = False,
 ) -> 'pd.DataFrame'
 {{< /highlight >}}
--- a/website/content/SDK/crypto/onchain/btc_supply/_index.rst
+++ b/website/content/SDK/crypto/onchain/btc_supply/_index.rst
@@ -38,7 +38,7 @@ crypto.onchain.btc_supply() -> pandas.core.frame.DataFrame
 {{< highlight python >}}
 crypto.onchain.btc_supply(
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/crypto/onchain/btc_transac/_index.rst
+++ b/website/content/SDK/crypto/onchain/btc_transac/_index.rst
@@ -38,7 +38,7 @@ crypto.onchain.btc_transac() -> pandas.core.frame.DataFrame
 {{< highlight python >}}
 crypto.onchain.btc_transac(
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/crypto/onchain/hr/_index.rst
+++ b/website/content/SDK/crypto/onchain/hr/_index.rst
@@ -17,7 +17,7 @@ crypto.onchain.hr(
    symbol: str,
    interval: str = '24h',
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -60,7 +60,7 @@ crypto.onchain.hr(
 crypto.onchain.hr(
    symbol: str,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    interval: str = '24h',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/crypto/ov/altindex/_index.rst
+++ b/website/content/SDK/crypto/ov/altindex/_index.rst
@@ -16,7 +16,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 crypto.ov.altindex(
    period: int = 30,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -59,7 +59,7 @@ crypto.ov.altindex(
 crypto.ov.altindex(
    period: int = 365,
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/crypto/ov/btcrb/_index.rst
+++ b/website/content/SDK/crypto/ov/btcrb/_index.rst
@@ -15,7 +15,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 {{< highlight python >}}
 crypto.ov.btcrb(
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 )
 {{< /highlight >}}
@@ -49,7 +49,7 @@ crypto.ov.btcrb(
 {{< highlight python >}}
 crypto.ov.btcrb(
    start_date: str = '2010-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/economy/events/_index.rst
+++ b/website/content/SDK/economy/events/_index.rst
@@ -13,8 +13,8 @@
 {{< highlight python >}}
 economy.events(
    countries: Union[List[str], str] = '',
-    start_date: str = '2022-11-10',
-    end_date: str = '2022-11-10',
+    start_date: str = '2022-11-14',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
--- a/website/content/SDK/economy/macro/_index.rst
+++ b/website/content/SDK/economy/macro/_index.rst
@@ -19,7 +19,7 @@ economy.macro(
    transform: str = '',
    start_date: str = '1900-01-01',
    end_date=datetime.date(
-    2022, 11, 10, chart: bool = False,
+    2022, 11, 14, chart: bool = False,
 ), symbol: str = '',
    chart: bool = False,
 ) -> Tuple[Any, Dict[Any, Dict[Any, Any]], str]
@@ -72,7 +72,7 @@ economy.macro(
    countries: list = None,
    transform: str = '',
    start_date: str = '1900-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    symbol: str = '',
    raw: bool = False,
    external_axes: Optional[List[axes]] = None,
--- a/website/content/SDK/economy/treasury/_index.rst
+++ b/website/content/SDK/economy/treasury/_index.rst
@@ -18,7 +18,7 @@ economy.treasury(
    maturities: list = None,
    frequency: str = 'monthly',
    start_date: str = '1900-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -65,7 +65,7 @@ economy.treasury(
    maturities: list = None,
    frequency: str = 'monthly',
    start_date: str = '1900-01-01',
-    end_date: str = '2022-11-10',
+    end_date: str = '2022-11-14',
    raw: bool = False,
    external_axes: Optional[List[axes]] = None,
    export: str = '',
--- a/website/content/SDK/etf/candle/_index.rst
+++ b/website/content/SDK/etf/candle/_index.rst
@@ -19,9 +19,9 @@ etf.candle(
    add_trend: bool = False,
    ma: Optional[Iterable[int]] = None,
    asset_type: str = '',
-    start_date: Union[datetime.datetime, str, NoneType] = '2019-11-06',
+    start_date: Union[datetime.datetime, str, NoneType] = '2019-11-10',
    interval: int = 1440,
-    end_date: Union[datetime.datetime, str, NoneType] = '2022-11-10',
+    end_date: Union[datetime.datetime, str, NoneType] = '2022-11-14',
    prepost: bool = False,
    source: str = 'YahooFinance',
    iexrange: str = 'ytd',
--- a/website/content/SDK/etf/load/_index.rst
+++ b/website/content/SDK/etf/load/_index.rst
@@ -13,9 +13,9 @@
 {{< highlight python >}}
 etf.load(
    symbol: str,
-    start_date: Union[datetime.datetime, str, NoneType] = '2019-11-06',
+    start_date: Union[datetime.datetime, str, NoneType] = '2019-11-10',
    interval: int = 1440,
-    end_date: Union[datetime.datetime, str, NoneType] = '2022-11-10',
+    end_date: Union[datetime.datetime, str, NoneType] = '2022-11-14',
    prepost: bool = False,
    source: str = 'YahooFinance',
    iexrange: str = 'ytd',
--- a/website/content/SDK/etf/news/_index.rst
+++ b/website/content/SDK/etf/news/_index.rst
@@ -16,7 +16,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 etf.news(
    query: str,
    limit: int = 10,
-    start_date: str = '2022-11-03',
+    start_date: str = '2022-11-07',
    show_newest: bool = True,
    sources: str = '',
    chart: bool = False,
@@ -60,7 +60,7 @@ etf.news(
 etf.news(
    query: str,
    limit: int = 3,
-    start_date: str = '2022-11-03',
+    start_date: str = '2022-11-07',
    show_newest: bool = True,
    sources: str = '',
    export: str = '',
--- a/website/content/SDK/forex/get_currency_list/_index.rst
+++ b/website/content/SDK/forex/get_currency_list/_index.rst
@@ -17,5 +17,5 @@ forex.get_currency_list() -> List
 .. raw:: html

    <p>
-    Load AV currency codes from a local file
+    Load AV currency codes from a local file.
    </p>
--- a/website/content/SDK/forex/load/_index.rst
+++ b/website/content/SDK/forex/load/_index.rst
@@ -16,7 +16,7 @@ forex.load(
    from_symbol: str,
    resolution: str = 'd',
    interval: str = '1day',
-    start_date: str = '2021-11-10',
+    start_date: str = '2021-11-14',
    source: str = 'YahooFinance',
    verbose: bool = False,
    chart: bool = False,
--- a/website/content/SDK/futures/historical/_index.rst
+++ b/website/content/SDK/futures/historical/_index.rst
@@ -53,7 +53,7 @@ futures.historical(
 futures.historical(
    symbols: List[str],
    expiry: str = '',
-    start_date: str = '2019-11-11',
+    start_date: str = '2019-11-15',
    raw: bool = False,
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
--- a/website/content/SDK/portfolio/_index.md
+++ b/website/content/SDK/portfolio/_index.md
@@ -1,7 +1,7 @@
 ---
 title: Introduction to Portfolio
 keywords: "portfolio, attribution, optimization, pnl, benchmark, return, volatility, metrics, broker, integration, report"
-excerpt: "The Introduction to Portfolio explains how to use the 
+excerpt: "The Introduction to Portfolio explains how to use the
 menu and provides a brief description of its sub-menus"
 geekdocCollapseSection: true
 ---
@@ -33,7 +33,7 @@ The SDK commands of the the menu:
 	<openbb>.portfolio.maxdd
 	<openbb>.portfolio.rvol
 	<openbb>.portfolio.rsharpe
-	<openbb>.portfolio.rsortino
+	<openbb>.portfolio.rsort
 	<openbb>.portfolio.rbeta
 	<openbb>.portfolio.summary
 	<openbb>.portfolio.skew
@@ -50,7 +50,7 @@ in the following:
 from openbb_terminal.sdk import Portfolio

 # Define your own orderbook location here
-orderbook_path = "Public_Equity_Orderbook.xlsx" 
+orderbook_path = "Public_Equity_Orderbook.xlsx"

 # Load in the transactions
 transactions = Portfolio.read_orderbook(orderbook_path)
@@ -58,7 +58,7 @@ P = Portfolio(transactions)
 P.generate_portfolio_data()

 # Load in the benchmark, by default this is the SPY ETF
-P.load_benchmark()
+P.set_benchmark()
 ```

 Note that the Excel sheet requires the following columns:
@@ -134,7 +134,7 @@ takes a bit longer to load.
 from openbb_terminal.sdk import Portfolio

 # Define your own orderbook location here
-orderbook_path = "Public_Equity_Orderbook_No_Categorization.xlsx" 
+orderbook_path = "Public_Equity_Orderbook_No_Categorization.xlsx"

 # Load in the transactions
 transactions = Portfolio.read_orderbook(orderbook_path)
@@ -142,7 +142,7 @@ P = Portfolio(transactions)
 P.generate_portfolio_data()

 # Load in the benchmark, by default this is the SPY ETF
-P.load_benchmark()
+P.set_benchmark()
 ```

 Then, we can show our performance compared to that of the benchmark.
--- a/website/content/SDK/portfolio/alloc/_index.md
+++ b/website/content/SDK/portfolio/alloc/_index.md
@@ -0,0 +1,6 @@
+---
+title: alloc
+keywords: ""
+excerpt: ""
+geekdocCollapseSection: true
+---
--- a/website/content/SDK/portfolio/alloc/assets/_index.rst
+++ b/website/content/SDK/portfolio/alloc/assets/_index.rst
@@ -0,0 +1,52 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.alloc.assets(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    tables: bool = False,
+    limit: int = 10,
+    recalculate: bool = False,
+    chart: bool = False,
+) -> Union[pandas.core.frame.DataFrame, Tuple[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame, pandas.core.frame.DataFrame]]
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Display portfolio asset allocation compared to the benchmark
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    tables: bool
+        Whether to include separate allocation tables
+    limit: int
+        The amount of assets you wish to show, by default this is set to 10
+    recalculate: bool
+        Flag to force recalculate allocation if already exists
+
+* **Returns**
+
+    Union[pd.DataFrame, Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]]
+        DataFrame with combined allocation plus individual allocation if tables is `True`.
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.alloc.assets(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/alloc/countries/_index.rst
+++ b/website/content/SDK/portfolio/alloc/countries/_index.rst
@@ -0,0 +1,51 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.alloc.countries(
+    portfolio_engine=None, limit: int = 10,
+    tables: bool = False,
+    recalculate: bool = False,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Display portfolio country allocation compared to the benchmark
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    tables: bool
+        Whether to include separate allocation tables
+    limit: int
+        The amount of assets you wish to show, by default this is set to 10
+    recalculate: bool
+        Flag to force recalculate allocation if already exists
+
+* **Returns**
+
+    Union[pd.DataFrame, Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]]
+        DataFrame with combined allocation plus individual allocation if tables is `True`.
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.alloc.countries(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/alloc/regions/_index.rst
+++ b/website/content/SDK/portfolio/alloc/regions/_index.rst
@@ -0,0 +1,51 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.alloc.regions(
+    portfolio_engine=None, limit: int = 10,
+    tables: bool = False,
+    recalculate: bool = False,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Display portfolio region allocation compared to the benchmark
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    tables: bool
+        Whether to include separate allocation tables
+    limit: int
+        The amount of assets you wish to show, by default this is set to 10
+    recalculate: bool
+        Flag to force recalculate allocation if already exists
+
+* **Returns**
+
+    Union[pd.DataFrame, Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]]
+        DataFrame with combined allocation plus individual allocation if tables is `True`.
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.alloc.regions(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/alloc/sectors/_index.rst
+++ b/website/content/SDK/portfolio/alloc/sectors/_index.rst
@@ -0,0 +1,51 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.alloc.sectors(
+    portfolio_engine=None, limit: int = 10,
+    tables: bool = False,
+    recalculate: bool = False,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Display portfolio sector allocation compared to the benchmark
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    tables: bool
+        Whether to include separate allocation tables
+    limit: int
+        The amount of assets you wish to show, by default this is set to 10
+    recalculate: bool
+        Flag to force recalculate allocation if already exists
+
+* **Returns**
+
+    Union[pd.DataFrame, Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]]
+        DataFrame with combined allocation plus individual allocation if tables is `True`.
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.alloc.sectors(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/bench/_index.rst
+++ b/website/content/SDK/portfolio/bench/_index.rst
@@ -0,0 +1,44 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.bench(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    symbol: str,
+    full_shares: bool = False,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Load benchmark into portfolio
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine object
+    symbol: str
+        Benchmark symbol to download data
+    full_shares: bool
+        Whether to mimic the portfolio trades exactly (partial shares) or round down the
+        quantity to the nearest number
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.bench(P, symbol="SPY")
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/calmar/_index.rst
+++ b/website/content/SDK/portfolio/calmar/_index.rst
@@ -1,39 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.calmar(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    window: int = 756,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Get calmar ratio
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-    window: int
-        Interval used for rolling values
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of calmar ratio of the benchmark and portfolio during different time periods
-    pd.Series
-        Series of calmar ratio data
--- a/website/content/SDK/portfolio/commonsense/_index.rst
+++ b/website/content/SDK/portfolio/commonsense/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.commonsense(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Get common sense ratio
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of the portfolios and the benchmarks common sense ratio during different time periods
--- a/website/content/SDK/portfolio/distr/_index.rst
+++ b/website/content/SDK/portfolio/distr/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.distr(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    chart: bool = False,
 )
@@ -28,14 +28,23 @@ portfolio.distr(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    chart: bool
       Flag to display chart


+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.distr(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -46,7 +55,7 @@ portfolio.distr(

 {{< highlight python >}}
 portfolio.distr(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    raw: bool = False,
    export: str = '',
--- a/website/content/SDK/portfolio/dret/_index.rst
+++ b/website/content/SDK/portfolio/dret/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.dret(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -28,8 +28,9 @@ portfolio.dret(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    chart: bool
@@ -39,6 +40,15 @@ portfolio.dret(
 * **Returns**

    pd.DataFrame
+        DataFrame with daily returns
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.dret(P)
+    {{< /highlight >}}

 |

@@ -50,7 +60,7 @@ portfolio.dret(

 {{< highlight python >}}
 portfolio.dret(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    raw: bool = False,
    limit: int = 10,
@@ -68,8 +78,9 @@ portfolio.dret(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    raw : False
--- a/website/content/SDK/portfolio/es/_index.rst
+++ b/website/content/SDK/portfolio/es/_index.rst
@@ -12,7 +12,7 @@

 {{< highlight python >}}
 portfolio.es(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    use_mean: bool = False,
    distribution: str = 'normal',
    percentile: float = 99.9,
@@ -28,8 +28,9 @@ portfolio.es(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    use_mean:
        if one should use the data mean return
    distribution: str
@@ -40,3 +41,12 @@ portfolio.es(
 * **Returns**

    pd.DataFrame
+        DataFrame with portfolio expected shortfall
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.es(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/gaintopain/_index.rst
+++ b/website/content/SDK/portfolio/gaintopain/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.gaintopain(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Get Pain-to-Gain ratio based on historical data
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of the portfolio's gain-to-pain ratio
--- a/website/content/SDK/portfolio/holdp/_index.rst
+++ b/website/content/SDK/portfolio/holdp/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.holdp(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    chart: bool = False,
 )
 {{< /highlight >}}
@@ -27,12 +27,21 @@ portfolio.holdp(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    chart: bool
       Flag to display chart


+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.holdp(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -43,7 +52,7 @@ portfolio.holdp(

 {{< highlight python >}}
 portfolio.holdp(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    unstack: bool = False,
    raw: bool = False,
    limit: int = 10,
@@ -61,8 +70,9 @@ portfolio.holdp(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    unstack: bool
        Individual assets over time
    raw : bool
--- a/website/content/SDK/portfolio/holdv/_index.rst
+++ b/website/content/SDK/portfolio/holdv/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.holdv(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -27,8 +27,9 @@ portfolio.holdv(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    chart: bool
       Flag to display chart

@@ -38,6 +39,14 @@ portfolio.holdv(
    pd.DataFrame
        DataFrame of holdings

+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.holdv(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -48,7 +57,7 @@ portfolio.holdv(

 {{< highlight python >}}
 portfolio.holdv(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    unstack: bool = False,
    raw: bool = False,
    limit: int = 10,
@@ -66,8 +75,9 @@ portfolio.holdv(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    unstack: bool
        Individual assets over time
    raw : bool
--- a/website/content/SDK/portfolio/information/_index.rst
+++ b/website/content/SDK/portfolio/information/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.information(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Get information ratio
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of the information ratio during different time periods
--- a/website/content/SDK/portfolio/kelly/_index.rst
+++ b/website/content/SDK/portfolio/kelly/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.kelly(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Gets kelly criterion
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of kelly criterion of the portfolio during different time periods
--- a/website/content/SDK/portfolio/kurtosis/_index.rst
+++ b/website/content/SDK/portfolio/kurtosis/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.kurtosis(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-) -> pandas.core.frame.DataFrame
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Class method that retrieves kurtosis for portfolio and benchmark selected
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame with kurtosis for portfolio and benchmark for different periods
--- a/website/content/SDK/portfolio/load/_index.rst
+++ b/website/content/SDK/portfolio/load/_index.rst
@@ -0,0 +1,51 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.load(
+    transactions_file_path: str,
+    benchmark_symbol: str = 'SPY',
+    full_shares: bool = False,
+    risk_free_rate: float = 0,
+    chart: bool = False,
+) -> openbb_terminal.portfolio.portfolio_model.PortfolioEngine
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get PortfolioEngine object
+    </p>
+
+* **Parameters**
+
+    transactions_file_path : str
+        Path to transactions file
+    benchmark_symbol : str
+        Benchmark ticker to download data
+    full_shares : bool
+        Whether to mimic the portfolio trades exactly (partial shares) or round down the
+        quantity to the nearest number
+    risk_free_rate : float
+        Risk free rate in float format
+
+* **Returns**
+
+    PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/max_drawdown_ratio/_index.rst
+++ b/website/content/SDK/portfolio/max_drawdown_ratio/_index.rst
@@ -1,79 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-To obtain charts, make sure to add :python:`chart = True` as the last parameter.
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.max_drawdown_ratio(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    is_returns: bool = False,
-    chart: bool = False,
-) -> pandas.core.series.Series
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Calculate the drawdown (MDD) of historical series.  Note that the calculation is done
-     on cumulative returns (or prices).  The definition of drawdown is
-
-     DD = (current value - rolling maximum) / rolling maximum
-    </p>
-
-* **Parameters**
-
-    data: pd.Series
-        Series of input values
-    is_returns: bool
-        Flag to indicate inputs are returns
-    chart: bool
-       Flag to display chart
-
-
-* **Returns**
-
-    pd.Series
-        Holdings series
-    pd.Series
-        Drawdown series
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting charts
-    </h3>
-
-{{< highlight python >}}
-portfolio.max_drawdown_ratio(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    export: str = '',
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Display maximum drawdown for multiple intervals
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-    export : str
-        Export data format
-    chart: bool
-       Flag to display chart
-
--- a/website/content/SDK/portfolio/maxdd/_index.rst
+++ b/website/content/SDK/portfolio/maxdd/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.maxdd(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    is_returns: bool = False,
    chart: bool = False,
 ) -> pandas.core.series.Series
@@ -46,6 +46,14 @@ portfolio.maxdd(
    pd.Series
        Drawdown series

+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.maxdd(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -56,7 +64,7 @@ portfolio.maxdd(

 {{< highlight python >}}
 portfolio.maxdd(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
@@ -71,8 +79,8 @@ portfolio.maxdd(

 * **Parameters**

-    portfolio : PortfolioModel
-        Portfolio object
+    portfolio : PortfolioEngine
+        PortfolioEngine object
    export: str
        Format to export data
    external_axes: plt.Axes
--- a/website/content/SDK/portfolio/maxdrawdown/_index.rst
+++ b/website/content/SDK/portfolio/maxdrawdown/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.maxdrawdown(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-) -> pandas.core.frame.DataFrame
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Class method that retrieves maximum drawdown ratio for portfolio and benchmark selected
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame with maximum drawdown for portfolio and benchmark for different periods
--- a/website/content/SDK/portfolio/metric/_index.md
+++ b/website/content/SDK/portfolio/metric/_index.md
@@ -0,0 +1,6 @@
+---
+title: metric
+keywords: ""
+excerpt: ""
+geekdocCollapseSection: true
+---
--- a/website/content/SDK/portfolio/metric/calmar/_index.rst
+++ b/website/content/SDK/portfolio/metric/calmar/_index.rst
@@ -0,0 +1,48 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.calmar(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    window: int = 756,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get calmar ratio
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    window: int
+        Interval used for rolling values
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of calmar ratio of the benchmark and portfolio during different time periods
+    pd.Series
+        Series of calmar ratio data
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.calmar(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/commonsense/_index.rst
+++ b/website/content/SDK/portfolio/metric/commonsense/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.commonsense(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get common sense ratio
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of the portfolios and the benchmarks common sense ratio during different time periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.commonsense(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/gaintopain/_index.rst
+++ b/website/content/SDK/portfolio/metric/gaintopain/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.gaintopain(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get Pain-to-Gain ratio based on historical data
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of the portfolio's gain-to-pain ratio
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.gaintopain(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/information/_index.rst
+++ b/website/content/SDK/portfolio/metric/information/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.information(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get information ratio
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of the information ratio during different time periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.information(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/jensens/_index.rst
+++ b/website/content/SDK/portfolio/metric/jensens/_index.rst
@@ -11,8 +11,8 @@
    </h3>

 {{< highlight python >}}
-portfolio.jensens(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+portfolio.metric.jensens(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    risk_free_rate: float = 0,
    window: str = '1y',
    chart: bool = False,
@@ -27,8 +27,9 @@ portfolio.jensens(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window: str
        Interval used for rolling values
    risk_free_rate: float
@@ -40,3 +41,11 @@ portfolio.jensens(
        DataFrame of jensens's alpha during different time windows
    pd.Series
        Series of jensens's alpha data
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.jensens(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/kelly/_index.rst
+++ b/website/content/SDK/portfolio/metric/kelly/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.kelly(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Gets kelly criterion
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of kelly criterion of the portfolio during different time periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.kelly(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/kurtosis/_index.rst
+++ b/website/content/SDK/portfolio/metric/kurtosis/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.kurtosis(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves kurtosis for portfolio and benchmark selected
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with kurtosis for portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.kurtosis(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/maxdrawdown/_index.rst
+++ b/website/content/SDK/portfolio/metric/maxdrawdown/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.maxdrawdown(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves maximum drawdown ratio for portfolio and benchmark selected
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with maximum drawdown for portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.maxdrawdown(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/payoff/_index.rst
+++ b/website/content/SDK/portfolio/metric/payoff/_index.rst
@@ -0,0 +1,48 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.payoff(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Gets payoff ratio
+
+    Returns
+    -------
+    pd.DataFrame
+        DataFrame of payoff ratio of the portfolio during different time periods
+
+    Examples
+    --------
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.payoff(P)
+    </p>
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of payoff ratio of the portfolio during different time periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.payoff(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/profitfactor/_index.rst
+++ b/website/content/SDK/portfolio/metric/profitfactor/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.profitfactor(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Gets profit factor
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of profit factor of the portfolio during different time periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.profitfactor(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/rsquare/_index.rst
+++ b/website/content/SDK/portfolio/metric/rsquare/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.rsquare(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves R2 Score for portfolio and benchmark selected
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with R2 Score between portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.rsquare(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/sharpe/_index.rst
+++ b/website/content/SDK/portfolio/metric/sharpe/_index.rst
@@ -0,0 +1,46 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.sharpe(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    risk_free_rate: float = 0,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves sharpe ratio for portfolio and benchmark selected
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    risk_free_rate: float
+        Risk free rate value
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with sharpe ratio for portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.sharpe(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/skew/_index.rst
+++ b/website/content/SDK/portfolio/metric/skew/_index.rst
@@ -0,0 +1,52 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.skew(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves skewness for portfolio and benchmark selected
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+    Returns
+    -------
+    pd.DataFrame
+        DataFrame with skewness for portfolio and benchmark for different periods
+
+    Examples
+    --------
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.skew(P)
+    </p>
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with skewness for portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.skew(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/sortino/_index.rst
+++ b/website/content/SDK/portfolio/metric/sortino/_index.rst
@@ -0,0 +1,46 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.sortino(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    risk_free_rate: float = 0,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves sortino ratio for portfolio and benchmark selected
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    risk_free_rate: float
+        Risk free rate value
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with sortino ratio for portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.sortino(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/tail/_index.rst
+++ b/website/content/SDK/portfolio/metric/tail/_index.rst
@@ -11,8 +11,8 @@
    </h3>

 {{< highlight python >}}
-portfolio.tail(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+portfolio.metric.tail(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: int = 252,
    chart: bool = False,
 )
@@ -26,9 +26,9 @@ portfolio.tail(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window: int
        Interval used for rolling values

@@ -40,3 +40,11 @@ portfolio.tail(
        Series of the portfolios rolling tail ratio
    pd.Series
        Series of the benchmarks rolling tail ratio
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.tail(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/trackerr/_index.rst
+++ b/website/content/SDK/portfolio/metric/trackerr/_index.rst
@@ -0,0 +1,48 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.trackerr(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    window: int = 252,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get tracking error
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+    window: int
+        Interval used for rolling values
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame of tracking errors during different time windows
+    pd.Series
+        Series of rolling tracking error
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.trackerr(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/metric/volatility/_index.rst
+++ b/website/content/SDK/portfolio/metric/volatility/_index.rst
@@ -0,0 +1,43 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.metric.volatility(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Method that retrieves volatility for portfolio and benchmark selected
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
+
+* **Returns**
+
+    pd.DataFrame
+        DataFrame with volatility for portfolio and benchmark for different periods
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.metric.volatility(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/mret/_index.rst
+++ b/website/content/SDK/portfolio/mret/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.mret(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -28,8 +28,9 @@ portfolio.mret(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    chart: bool
@@ -39,6 +40,15 @@ portfolio.mret(
 * **Returns**

    pd.DataFrame
+        DataFrame with monthly returns
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.mret(P)
+    {{< /highlight >}}

 |

@@ -50,7 +60,7 @@ portfolio.mret(

 {{< highlight python >}}
 portfolio.mret(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    raw: bool = False,
    show_vals: bool = False,
@@ -68,8 +78,9 @@ portfolio.mret(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    raw : False
--- a/website/content/SDK/portfolio/om/_index.rst
+++ b/website/content/SDK/portfolio/om/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.om(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    threshold_start: float = 0,
    threshold_end: float = 1.5,
    chart: bool = False,
@@ -29,8 +29,9 @@ portfolio.om(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    threshold_start: float
        annualized target return threshold start of plotted threshold range
    threshold_end: float
@@ -42,6 +43,15 @@ portfolio.om(
 * **Returns**

    pd.DataFrame
+        DataFrame with portfolio omega ratio
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.om(P)
+    {{< /highlight >}}

 |

@@ -53,7 +63,7 @@ portfolio.om(

 {{< highlight python >}}
 portfolio.om(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    threshold_start: float = 0,
    threshold_end: float = 1.5,
    chart: bool = False,
@@ -68,8 +78,9 @@ portfolio.om(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    threshold_start: float
        annualized target return threshold start of plotted threshold range
    threshold_end: float
--- a/website/content/SDK/portfolio/payoff/_index.rst
+++ b/website/content/SDK/portfolio/payoff/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.payoff(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Gets payoff ratio
-
-    Returns
-    -------
-    pd.DataFrame
-        DataFrame of payoff ratio of the portfolio during different time periods
-    </p>
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of payoff ratio of the portfolio during different time periods
--- a/website/content/SDK/portfolio/perf/_index.rst
+++ b/website/content/SDK/portfolio/perf/_index.rst
@@ -12,7 +12,7 @@

 {{< highlight python >}}
 portfolio.perf(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    show_all_trades: bool = False,
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -26,11 +26,21 @@ portfolio.perf(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    show_all_trades: bool
        Whether to also show all trades made and their performance (default is False)

 * **Returns**

    pd.DataFrame
+        DataFrame with portfolio performance vs the benchmark
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.perf(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/profitfactor/_index.rst
+++ b/website/content/SDK/portfolio/profitfactor/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.profitfactor(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Gets profit factor
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of profit factor of the portfolio during different time periods
--- a/website/content/SDK/portfolio/rbeta/_index.rst
+++ b/website/content/SDK/portfolio/rbeta/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.rbeta(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = '1y',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -28,8 +28,8 @@ portfolio.rbeta(

 * **Parameters**

-    portfolio : PortfolioModel
-        Portfolio object
+    portfolio : PortfolioEngine
+        PortfolioEngine object
    window: string
        Interval used for rolling values.
        Possible options: mtd, qtd, ytd, 1d, 5d, 10d, 1m, 3m, 6m, 1y, 3y, 5y, 10y.
@@ -42,6 +42,14 @@ portfolio.rbeta(
    pd.DataFrame
        DataFrame of the portfolio's rolling beta

+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.rbeta(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -52,7 +60,7 @@ portfolio.rbeta(

 {{< highlight python >}}
 portfolio.rbeta(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = '1y',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
@@ -68,8 +76,8 @@ portfolio.rbeta(

 * **Parameters**

-    portfolio : PortfolioModel
-        Portfolio object
+    portfolio : PortfolioEngine
+        PortfolioEngine object
    window: str
        interval for window to consider
        Possible options: mtd, qtd, ytd, 1d, 5d, 10d, 1m, 3m, 6m, 1y, 3y, 5y, 10y.
--- a/website/content/SDK/portfolio/rsharpe/_index.rst
+++ b/website/content/SDK/portfolio/rsharpe/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.rsharpe(
-    portfolio: pandas.core.frame.DataFrame,
+    portfolio_engine: pandas.core.frame.DataFrame,
    risk_free_rate: float = 0,
    window: str = '1y',
    chart: bool = False,
@@ -45,6 +45,14 @@ portfolio.rsharpe(
    pd.DataFrame
        Rolling sharpe ratio DataFrame

+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.rsharpe(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -55,7 +63,7 @@ portfolio.rsharpe(

 {{< highlight python >}}
 portfolio.rsharpe(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    risk_free_rate: float = 0,
    window: str = '1y',
    export: str = '',
@@ -72,8 +80,8 @@ portfolio.rsharpe(

 * **Parameters**

-    portfolio : PortfolioModel
-        Portfolio object
+    portfolio : PortfolioEngine
+        PortfolioEngine object
    risk_free_rate: float
        Value to use for risk free rate in sharpe/other calculations
    window: str
--- a/website/content/SDK/portfolio/rsort/_index.rst
+++ b/website/content/SDK/portfolio/rsort/_index.rst
@@ -0,0 +1,95 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+To obtain charts, make sure to add :python:`chart = True` as the last parameter.
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.rsort(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    risk_free_rate: float = 0,
+    window: str = '1y',
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get rolling sortino
+    </p>
+
+* **Parameters**
+
+    portfolio : PortfolioEngine
+        PortfolioEngine object
+    window: str
+        interval for window to consider
+        Possible options: mtd, qtd, ytd, 1d, 5d, 10d, 1m, 3m, 6m, 1y, 3y, 5y, 10y
+    risk_free_rate: float
+        Value to use for risk free rate in sharpe/other calculations
+    chart: bool
+       Flag to display chart
+
+
+* **Returns**
+
+    pd.DataFrame
+        Rolling sortino ratio DataFrame
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.rsortino(P)
+    {{< /highlight >}}
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting charts
+    </h3>
+
+{{< highlight python >}}
+portfolio.rsort(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    risk_free_rate: float = 0,
+    window: str = '1y',
+    export: str = '',
+    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
+    chart: bool = False,
+)
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Display rolling sortino
+    </p>
+
+* **Parameters**
+
+    portfolio : PortfolioEngine
+        PortfolioEngine object
+    risk_free_rate: float
+        Value to use for risk free rate in sharpe/other calculations
+    window: str
+        interval for window to consider
+    export: str
+        Export to file
+    external_axes: Optional[List[plt.Axes]]
+        Optional axes to display plot on
+    chart: bool
+       Flag to display chart
+
--- a/website/content/SDK/portfolio/rsortino/_index.rst
+++ b/website/content/SDK/portfolio/rsortino/_index.rst
@@ -13,8 +13,8 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
    </h3>

 {{< highlight python >}}
-portfolio.rsortino(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+portfolio.rsort(
+    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    risk_free_rate: float = 0,
    window: str = '1y',
    chart: bool = False,
@@ -29,7 +29,7 @@ portfolio.rsortino(

 * **Parameters**

-    portfolio : PortfolioModel
+    portfolio : PortfolioEngine
        Portfolio object
    window: str
        interval for window to consider
@@ -54,8 +54,8 @@ portfolio.rsortino(
    </h3>

 {{< highlight python >}}
-portfolio.rsortino(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+portfolio.rsort(
+    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    risk_free_rate: float = 0,
    window: str = '1y',
    export: str = '',
@@ -72,7 +72,7 @@ portfolio.rsortino(

 * **Parameters**

-    portfolio : PortfolioModel
+    portfolio : PortfolioEngine
        Portfolio object
    risk_free_rate: float
        Value to use for risk free rate in sharpe/other calculations
@@ -84,4 +84,3 @@ portfolio.rsortino(
        Optional axes to display plot on
    chart: bool
       Flag to display chart
-
--- a/website/content/SDK/portfolio/rsquare/_index.rst
+++ b/website/content/SDK/portfolio/rsquare/_index.rst
@@ -12,7 +12,7 @@

 {{< highlight python >}}
 portfolio.rsquare(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
--- a/website/content/SDK/portfolio/rvol/_index.rst
+++ b/website/content/SDK/portfolio/rvol/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.rvol(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = '1y',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -28,8 +28,9 @@ portfolio.rvol(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        Rolling window size to use
        Possible options: mtd, qtd, ytd, 1d, 5d, 10d, 1m, 3m, 6m, 1y, 3y, 5y, 10y
@@ -37,6 +38,14 @@ portfolio.rvol(
       Flag to display chart


+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.rvol(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -47,7 +56,7 @@ portfolio.rvol(

 {{< highlight python >}}
 portfolio.rvol(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = '1y',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
@@ -63,8 +72,8 @@ portfolio.rvol(

 * **Parameters**

-    portfolio : PortfolioModel
-        Portfolio object
+    portfolio : PortfolioEngine
+        PortfolioEngine object
    interval: str
        interval for window to consider
    export: str
--- a/website/content/SDK/portfolio/sharpe/_index.rst
+++ b/website/content/SDK/portfolio/sharpe/_index.rst
@@ -1,37 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.sharpe(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    risk_free_rate: float = 0,
-    chart: bool = False,
-) -> pandas.core.frame.DataFrame
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Class method that retrieves sharpe ratio for portfolio and benchmark selected
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-    risk_free_rate: float
-        Risk free rate value
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame with sharpe ratio for portfolio and benchmark for different periods
--- a/website/content/SDK/portfolio/show/_index.rst
+++ b/website/content/SDK/portfolio/show/_index.rst
@@ -0,0 +1,42 @@
+.. role:: python(code)
+    :language: python
+    :class: highlight
+
+|
+
+.. raw:: html
+
+    <h3>
+    > Getting data
+    </h3>
+
+{{< highlight python >}}
+portfolio.show(
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
+    chart: bool = False,
+) -> pandas.core.frame.DataFrame
+{{< /highlight >}}
+
+.. raw:: html
+
+    <p>
+    Get portfolio transactions
+    </p>
+
+* **Parameters**
+
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine object
+
+* **Returns**
+
+    pd.DataFrame
+        Portfolio transactions
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.show(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/skew/_index.rst
+++ b/website/content/SDK/portfolio/skew/_index.rst
@@ -1,37 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.skew(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-) -> pandas.core.frame.DataFrame
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Class method that retrieves skewness for portfolio and benchmark selected
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-    Returns
-    -------
-    pd.DataFrame
-        DataFrame with skewness for portfolio and benchmark for different periods
-    </p>
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame with skewness for portfolio and benchmark for different periods
--- a/website/content/SDK/portfolio/sortino/_index.rst
+++ b/website/content/SDK/portfolio/sortino/_index.rst
@@ -1,37 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.sortino(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    risk_free_rate: float = 0,
-    chart: bool = False,
-) -> pandas.core.frame.DataFrame
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Class method that retrieves sortino ratio for portfolio and benchmark selected
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-    risk_free_rate: float
-        Risk free rate value
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame with sortino ratio for portfolio and benchmark for different periods
--- a/website/content/SDK/portfolio/summary/_index.rst
+++ b/website/content/SDK/portfolio/summary/_index.rst
@@ -12,7 +12,7 @@

 {{< highlight python >}}
 portfolio.summary(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    risk_free_rate: float = 0,
    chart: bool = False,
@@ -22,13 +22,14 @@ portfolio.summary(
 .. raw:: html

    <p>
-    Get summary portfolio and benchmark returns
+    Get portfolio and benchmark returns summary
    </p>

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    risk_free_rate : float
@@ -37,3 +38,12 @@ portfolio.summary(
 * **Returns**

    pd.DataFrame
+        DataFrame with portfolio and benchmark returns summary
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.summary(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/trackerr/_index.rst
+++ b/website/content/SDK/portfolio/trackerr/_index.rst
@@ -1,39 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.trackerr(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    window: int = 252,
-    chart: bool = False,
-)
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Get tracking error
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-    window: int
-        Interval used for rolling values
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame of tracking errors during different time windows
-    pd.Series
-        Series of rolling tracking error
--- a/website/content/SDK/portfolio/var/_index.rst
+++ b/website/content/SDK/portfolio/var/_index.rst
@@ -12,7 +12,7 @@

 {{< highlight python >}}
 portfolio.var(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    use_mean: bool = False,
    adjusted_var: bool = False,
    student_t: bool = False,
@@ -29,8 +29,9 @@ portfolio.var(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    use_mean: bool
        if one should use the data mean return
    adjusted_var: bool
@@ -43,3 +44,12 @@ portfolio.var(
 * **Returns**

    pd.DataFrame
+        DataFrame with portfolio VaR
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.var(P)
+    {{< /highlight >}}
--- a/website/content/SDK/portfolio/volatility/_index.rst
+++ b/website/content/SDK/portfolio/volatility/_index.rst
@@ -1,34 +0,0 @@
-.. role:: python(code)
-    :language: python
-    :class: highlight
-
-|
-
-.. raw:: html
-
-    <h3>
-    > Getting data
-    </h3>
-
-{{< highlight python >}}
-portfolio.volatility(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
-    chart: bool = False,
-) -> pandas.core.frame.DataFrame
-{{< /highlight >}}
-
-.. raw:: html
-
-    <p>
-    Class method that retrieves volatility for portfolio and benchmark selected
-    </p>
-
-* **Parameters**
-
-    portfolio: Portfolio
-        Portfolio object with trades loaded
-
-* **Returns**
-
-    pd.DataFrame
-        DataFrame with volatility for portfolio and benchmark for different periods
--- a/website/content/SDK/portfolio/yret/_index.rst
+++ b/website/content/SDK/portfolio/yret/_index.rst
@@ -14,10 +14,10 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 portfolio.yret(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    chart: bool = False,
-)
+) -> pandas.core.frame.DataFrame
 {{< /highlight >}}

 .. raw:: html
@@ -28,14 +28,28 @@ portfolio.yret(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    chart: bool
       Flag to display chart


+* **Returns**
+
+    pd.DataFrame
+        DataFrame with yearly returns
+
+* **Examples**
+
+    {{< highlight python >}}
+    >>> from openbb_terminal.sdk import openbb
+    >>> P = openbb.portfolio.load("openbb_terminal/miscellaneous/portfolio_examples/holdings/example.csv")
+    >>> openbb.portfolio.yret(P)
+    {{< /highlight >}}
+
 |

 .. raw:: html
@@ -46,7 +60,7 @@ portfolio.yret(

 {{< highlight python >}}
 portfolio.yret(
-    portfolio: openbb_terminal.portfolio.portfolio_model.PortfolioModel,
+    portfolio_engine: openbb_terminal.portfolio.portfolio_model.PortfolioEngine,
    window: str = 'all',
    raw: bool = False,
    export: str = '',
@@ -63,8 +77,9 @@ portfolio.yret(

 * **Parameters**

-    portfolio: Portfolio
-        Portfolio object with trades loaded
+    portfolio_engine: PortfolioEngine
+        PortfolioEngine class instance, this will hold transactions and perform calculations.
+        Use `portfolio.load` to create a PortfolioEngine.
    window : str
        interval to compare cumulative returns and benchmark
    raw : False
--- a/website/content/SDK/stocks/ba/cnews/_index.rst
+++ b/website/content/SDK/stocks/ba/cnews/_index.rst
@@ -13,8 +13,8 @@
 {{< highlight python >}}
 stocks.ba.cnews(
    symbol: str,
-    start_date: str = '2022-10-11',
-    end_date: str = '2022-11-10',
+    start_date: str = '2022-10-15',
+    end_date: str = '2022-11-14',
    chart: bool = False,
 ) -> List[Dict]
 {{< /highlight >}}
--- a/website/content/SDK/stocks/ba/hist/_index.rst
+++ b/website/content/SDK/stocks/ba/hist/_index.rst
@@ -15,8 +15,8 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 {{< highlight python >}}
 stocks.ba.hist(
    symbol: str,
-    start_date: str = '2022-11-03',
-    end_date: str = '2022-11-10',
+    start_date: str = '2022-11-07',
+    end_date: str = '2022-11-14',
    number: int = 100,
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -61,8 +61,8 @@ stocks.ba.hist(
 {{< highlight python >}}
 stocks.ba.hist(
    symbol: str,
-    start_date: str = '2022-11-03',
-    end_date: str = '2022-11-10',
+    start_date: str = '2022-11-07',
+    end_date: str = '2022-11-14',
    number: int = 100,
    raw: bool = False,
    limit: int = 10,
--- a/website/content/SDK/stocks/ba/trend/_index.rst
+++ b/website/content/SDK/stocks/ba/trend/_index.rst
@@ -14,7 +14,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.

 {{< highlight python >}}
 stocks.ba.trend(
-    start_date: str = '2022-11-10',
+    start_date: str = '2022-11-14',
    hour: int = 0,
    number: int = 10,
    chart: bool = False,
@@ -58,7 +58,7 @@ stocks.ba.trend(

 {{< highlight python >}}
 stocks.ba.trend(
-    start_date: str = '2022-11-10',
+    start_date: str = '2022-11-14',
    hour: int = 0,
    number: int = 10,
    limit: int = 10,
--- a/website/content/SDK/stocks/ca/hcorr/_index.rst
+++ b/website/content/SDK/stocks/ca/hcorr/_index.rst
@@ -15,7 +15,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 {{< highlight python >}}
 stocks.ca.hcorr(
    similar: List[str],
-    start_date: str = '2021-11-09',
+    start_date: str = '2021-11-13',
    candle_type: str = 'a',
    chart: bool = False,
 )
@@ -52,7 +52,7 @@ stocks.ca.hcorr(
 {{< highlight python >}}
 stocks.ca.hcorr(
    similar: List[str],
-    start_date: str = '2021-11-09',
+    start_date: str = '2021-11-13',
    candle_type: str = 'a',
    display_full_matrix: bool = False,
    raw: bool = False,
--- a/website/content/SDK/stocks/ca/hist/_index.rst
+++ b/website/content/SDK/stocks/ca/hist/_index.rst
@@ -15,7 +15,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 {{< highlight python >}}
 stocks.ca.hist(
    similar: List[str],
-    start_date: str = '2021-11-09',
+    start_date: str = '2021-11-13',
    candle_type: str = 'a',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
@@ -57,7 +57,7 @@ stocks.ca.hist(
 {{< highlight python >}}
 stocks.ca.hist(
    similar: List[str],
-    start_date: str = '2021-11-09',
+    start_date: str = '2021-11-13',
    candle_type: str = 'a',
    normalize: bool = True,
    export: str = '',
--- a/website/content/SDK/stocks/ca/volume/_index.rst
+++ b/website/content/SDK/stocks/ca/volume/_index.rst
@@ -15,7 +15,7 @@ To obtain charts, make sure to add :python:`chart = True` as the last parameter.
 {{< highlight python >}}
 stocks.ca.volume(
    similar: List[str],
-    start_date: str = '2021-11-09',
+    start_date: str = '2021-11-13',
    chart: bool = False,
 ) -> pandas.core.frame.DataFrame
 {{< /highlight >}}
@@ -49,7 +49,7 @@ stocks.ca.volume(
 {{< highlight python >}}
 stocks.ca.volume(
    similar: List[str],
-    start_date: str = '2021-11-09',
+    start_date: str = '2021-11-13',
    export: str = '',
    external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None,
    chart: bool = False,
--- a/website/content/SDK/stocks/candle/_index.rst
+++ b/website/content/SDK/stocks/candle/_index.rst
@@ -19,9 +19,9 @@ stocks.candle(
    add_trend: bool = False,
    ma: Optional[Iterable[int]] = None,
    asset_type: str = '',
-    start_date: Union[datetime.datetime, str, NoneType] = '2019-11-06',
+    start_date: Union[datetime.datetime, str, NoneType] = '2019-11-10',
    interval: int = 1440,
-    end_date: Union[datetime.datetime, str, NoneType] = '2022-11-10',
+    end_date: Union[datetime.datetime, str, NoneType] = '2022-11-14',
    prepost: bool = False,
    source: str = 'YahooFinance',
    iexrange: str = 'ytd',
--- a/Show More
+++ b/Show More