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Merge branch 'develop' of https://github.com/OpenBB-finance/OpenBBTerminal into develop

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This commit is contained in:
James Maslek
2023-05-04 14:51:02 -04:00
parent c01af20a6f 0bcf3629a8
commit 7d317ce3ab
4 changed files with 411 additions and 791 deletions
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3
openbb_terminal/economy/finviz_model.py
View File

@@ -92,7 +92,7 @@ def get_valuation_data(
try:
group = GROUPS[group]
df_group = valuation.Valuation().screener_view(group=group)
df_group.columns = [col.replace(" ", "") for col in df_group.columns]
df_group.columns = [col.replace(" ", "").strip() for col in df_group.columns]
df_group = df_group.sort_values(by=sortby, ascending=ascend)
df_group.fillna("", inplace=True)
@@ -156,6 +156,7 @@ def get_performance_data(
"Rel Volume": "RelVolume",
}
)
df_group.columns = [col.strip() for col in df_group.columns]
df_group["Week"] = df_group["Week"].apply(lambda x: float(x.strip("%")) / 100)
df_group = df_group.sort_values(by=sortby, ascending=ascend)
df_group.fillna("", inplace=True)

123
openbb_terminal/reports/templates/equity.ipynb vendored
View File

@@ -58,11 +58,13 @@
"\n",
"user = get_current_user()\n",
"\n",
"cfg.theme = TerminalStyle(\n",
" user.preferences.MPL_STYLE,\n",
" user.preferences.PMF_STYLE,\n",
" user.preferences.RICH_STYLE,\n",
")"
"from openbb_terminal import theme\n",
"\n",
"#cfg.theme = TerminalStyle(\n",
"# user.preferences.MPL_STYLE,\n",
"# user.preferences.PMF_STYLE,\n",
"# user.preferences.RICH_STYLE,\n",
"#)"
]
},
{
@@ -97,7 +99,7 @@
"source": [
"# Parameters that will be replaced when calling this notebook\n",
"# Do not leave parameters blank as notebook will not run otherwise\n",
"symbol = \"IONQ\"\n",
"symbol = \"FRC\"\n",
"report_name = f\"Equity report for {symbol}\""
]
},
@@ -142,7 +144,7 @@
"metadata": {},
"outputs": [],
"source": [
"info = openbb.stocks.fa.data(symbol=symbol).transpose()\n",
"info = openbb.stocks.fa.overview(symbol=symbol, source=\"Finviz\").transpose()\n",
"\n",
"info\n",
"try:\n",
@@ -183,7 +185,7 @@
" df_quarter_earnings,\n",
" df_quarter_revenues,\n",
") = openbb.stocks.fa.est(symbol=symbol)\n",
"df_quarter_revenues"
"df_quarter_revenues.transpose()"
]
},
{
@@ -204,14 +206,14 @@
"metadata": {},
"outputs": [],
"source": [
"tables = openbb.etf.news(info[\"Short name\"][0], 5) if \"Short name\" in info else symbol\n",
"tables = openbb.stocks.news(symbol)\n",
"\n",
"for table in tables:\n",
" if not isinstance(table, pd.DataFrame):\n",
" continue\n",
"\n",
" table[0].loc[\"link\"] = (\n",
" table[0].loc[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
" table[0].loc[\"URL\"] = (\n",
" table[0].loc[\"URL\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
" )"
]
},
@@ -222,7 +224,7 @@
"metadata": {},
"outputs": [],
"source": [
"quote_data = openbb.stocks.quote([symbol])\n",
"quote_data = info[[\"Price\", \"Prev Close\", \"Change\", \"Volume\", \"52W Range\", \"Perf YTD\"]]\n",
"quote_data"
]
},
@@ -238,28 +240,6 @@
"df_institutional_shareholders"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e101e24e",
"metadata": {},
"outputs": [],
"source": [
"openbb.stocks.fa.shrs(symbol)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "51dfd9d2",
"metadata": {},
"outputs": [],
"source": [
"df_institutional_shareholders = openbb.stocks.fa.shrs(symbol)\n",
"df_institutional_shareholders.index += 1\n",
"df_institutional_shareholders"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -267,10 +247,14 @@
"metadata": {},
"outputs": [],
"source": [
"df_sec_filings = openbb.stocks.fa.sec(symbol)[\n",
" [\"Company Name\", \"Reporting Owner\", \"Form Type\", \"Period\"]\n",
"].head(5)\n",
"df_sec_filings"
"#this command works 1/2 the time - really need to fix this - but this will catch the errors and stop it from breaking the report\n",
"try:\n",
" df_sec_filings = openbb.stocks.fa.sec(symbol)[\n",
" [\"Company Name\", \"Reporting Owner\", \"Form Type\", \"Period\", \"View\"]\n",
" ].head(5)\n",
" df_sec_filings\n",
"except:\n",
" df_sec_filings = \"Error with Nasdaq API\""
]
},
{
@@ -280,25 +264,25 @@
"metadata": {},
"outputs": [],
"source": [
"df_analyst = openbb.stocks.fa.analyst(symbol=symbol)\n",
"print(df_analyst)\n",
"if not df_analyst.empty:\n",
" if \"target\" in df_analyst.columns:\n",
" if \"target_to\" in df_analyst.columns:\n",
" df_analyst[\"target\"] = df_analyst[\"target_to\"].combine_first(\n",
" df_analyst[\"target\"]\n",
" )\n",
" else:\n",
" df_analyst[\"target\"] = df_analyst[\"target\"]\n",
" df_analyst = df_analyst[[\"category\", \"analyst\", \"rating\", \"target\"]].rename(\n",
" columns={\n",
" \"category\": \"Category\",\n",
" \"analyst\": \"Analyst\",\n",
" \"rating\": \"Rating\",\n",
" \"target\": \"Price Target\",\n",
" }\n",
" )\n",
"df_analyst"
"df_analyst = openbb.stocks.fa.pt(symbol=symbol).sort_index(ascending = False)\n",
"#print(df_analyst)\n",
"#if not df_analyst.empty:\n",
"# if \"target\" in df_analyst.columns:\n",
"# if \"target_to\" in df_analyst.columns:\n",
"# df_analyst[\"target\"] = df_analyst[\"target_to\"].combine_first(\n",
"# df_analyst[\"target\"]\n",
"# )\n",
"# else:\n",
"# df_analyst[\"target\"] = df_analyst[\"target\"]\n",
"# df_analyst = df_analyst[[\"category\", \"analyst\", \"rating\", \"target\"]].rename(\n",
"# columns={\n",
"# \"category\": \"Category\",\n",
"# \"analyst\": \"Analyst\",\n",
"# \"rating\": \"Rating\",\n",
"# \"target\": \"Price Target\",\n",
"# }\n",
"# )\n",
"df_analyst.head(10)"
]
},
{
@@ -469,7 +453,7 @@
"metadata": {},
"outputs": [],
"source": [
"similar_companies = openbb.stocks.ca.similar(symbol, source=\"Polygon\")\n",
"similar_companies = openbb.stocks.ca.similar(symbol, source=\"Finviz\")[0:5]\n",
"if similar_companies:\n",
" similar_companies.append(symbol)"
]
@@ -666,7 +650,7 @@
"metadata": {},
"outputs": [],
"source": [
"df = openbb.stocks.fa.pt(symbol=symbol)\n",
"df = df_analyst.copy()\n",
"avg_ratings_last_30_days = 0\n",
"days = 0\n",
"if not df.empty:\n",
@@ -840,6 +824,7 @@
"ticker_data_all = openbb.stocks.load(\n",
" symbol=symbol,\n",
" start_date=datetime.datetime.now() - datetime.timedelta(days=5 * 12 * 21),\n",
" verbose = False\n",
")\n",
"ticker_data_all[\"Returns\"] = ticker_data_all[\"Adj Close\"].pct_change()"
]
@@ -889,8 +874,8 @@
"metadata": {},
"outputs": [],
"source": [
"income_df = openbb.stocks.fa.income(symbol, source=\"FinancialModelingPrep\")\n",
"data_df = openbb.stocks.fa.data(symbol)\n",
"income_df = openbb.stocks.fa.income(symbol, source = 'FinancialModelingPrep')\n",
"data_df = openbb.stocks.fa.overview(symbol, source = 'FinancialModelingPrep')\n",
"mgmt_df = openbb.stocks.fa.mgmt(symbol)\n",
"try:\n",
" if not mgmt_df.empty:\n",
@@ -1029,7 +1014,7 @@
"<style>\n",
"@font-face {{\n",
" font-family: \"Fira Code\";\n",
" src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/FiraCode-Regular.ttf\") format(\"truetype\");\n",
" src: url(\"{(OpenBBFigure.plotlyjs_path.parent.parent / \"web\"/\"css\").as_uri()}/fonts/Consolas-Regular.ttf\") format(\"truetype\");\n",
" font-weight: 400 700;\n",
" font-stretch: 50%;\n",
"}}\n",
@@ -1162,12 +1147,12 @@
" htmlcode += widgets.row([widgets.h(3, \"Analyst Ratings\") + df_analyst.to_html()])\n",
"except:\n",
" pass\n",
"try:\n",
" htmlcode += widgets.row(\n",
" [widgets.h(3, \"Analyst Recommendations\") + df_rating.to_html()]\n",
" )\n",
"except:\n",
" pass\n",
"#try:\n",
"# htmlcode += widgets.row(\n",
"# [widgets.h(3, \"Analyst Recommendations\") + df_rating.to_html()]\n",
"# )\n",
"#except:\n",
"# pass\n",
"\n",
"body += widgets.add_tab(\"Analyst Opinions\", htmlcode)\n",
"\n",
@@ -1405,7 +1390,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.5"
"version": "3.10.8"
},
"vscode": {
"interpreter": {

642
website/content/sdk/usage/intros/stocks/fundamental-analysis.md vendored
View File

@@ -3,10 +3,9 @@ title: Fundamental Analysis
keywords: [fundamentals, fundamental, fa, ratios, earnings, balance, income, cash, statement, statements, sec, multiples, price, ebitda, ebitdam, revenue, quarter, annual, change, company, performance, filing, filings, 10K, 8K, audit, audited, due diligence, research, company, ticker, analyst, rating, rot, pt, est, sec, supplier, customer, arktrades, ratings, analysts, filings, form, forms, customers, suppliers, alphavantage, EODHD, financial modeling prep, polygon, how to, usage, examples, sdk]
description: This guide introduces the Fundamental Analysis menu within the Stocks menu, briefly explains the features, and provides examples in context.
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="Fundamental Analysis - SDK | OpenBB Docs" />
`<HeadTitle title="Fundamental Analysis - SDK | OpenBB Docs" />`
The FA module provides programmatic access to the commands from within the OpenBB Terminal. To get the most out of these functions, we recommend obtaining API keys from:
@@ -15,62 +14,109 @@ The FA module provides programmatic access to the commands from within the OpenB
- Financial Modeling Prep
- Polygon
View [this page](https://docs.openbb.co/terminal/usage/guides/api-keys) for a list of all API sources used across the platform.
View [this page](https://docs.openbb.co/sdk/usage/guides/api-keys) for a list of all API sources used across the platform.
## How to Use
## The FA Module
The contextual help will be activated upon entering ., after, openbb.stocks.fa. A brief description below highlights the functions within the `fa` module.
A brief description below highlights the properties of the `fa` module.
| Path | Description |
| :---------------------------------|----------------------------------------------: |
| openbb.stocks.fa.analysis | Analysis SEC Fillings with Machine Learning |
| openbb.stocks.fa.balance | Company Balance Sheet |
| openbb.stocks.fa.cal | Calendar Earnings and Estimates |
| openbb.stocks.fa.cash | Company Cash Flows |
| openbb.stocks.fa.data | Fundamental and Technical Data |
| openbb.stocks.fa.dcfc | Shows DCF Values for a Ticker |
| openbb.stocks.fa.divs | Historical Dividends for a Company |
| openbb.stocks.fa.dupont | Detailed ROE Breakdown |
| openbb.stocks.fa.earnings | Earnings Data and EPS |
| openbb.stocks.fa.enterprise | Company Enterprise Value |
| openbb.stocks.fa.fama_coe | Fama/French value for Cost of Equity |
| openbb.stocks.fa.fraud | Key Fraud Ratios |
| openbb.stocks.fa.growth | Growth of Financial Statement Items |
| openbb.stocks.fa.hq | HQ Location for Company |
| openbb.stocks.fa.income | Company Income Statement |
| openbb.stocks.fa.info | Information About a Company |
| openbb.stocks.fa.key | Company Key Metrics |
| openbb.stocks.fa.metrics | Key Metrics Over Time |
| openbb.stocks.fa.mgmt | Company Management Team |
| openbb.stocks.fa.mktcap | Estimated Market Cap |
| openbb.stocks.fa.overview | Overview of the Company |
| openbb.stocks.fa.profile | Company Profile |
| openbb.stocks.fa.ratios | In-Depth Ratios over Time |
| openbb.stocks.fa.score | Investing Score from Warren Buffet |
| openbb.stocks.fa.shrs | Shareholders (Insiders, Institutions, Funds) |
| openbb.stocks.fa.splits | Stock Splits and Reverse Splits Since IPO |
| openbb.stocks.fa.sust | Sustainability Values |
|openbb.stocks.fa.analyst |Analyst Prices and Ratings |
|openbb.stocks.fa.arktrades |Ark Trades for the Ticker |
|openbb.stocks.fa.customer |List of Customers |
|openbb.stocks.fa.est |Earnings Estimates |
|openbb.stocks.fa.pt |Historical Price Targets |
|openbb.stocks.fa.rating |Daily Ratings |
|openbb.stocks.fa.rot |Historical Number of Analysts and Ratings |
|openbb.stocks.fa.sec |List of SEC Filings |
|openbb.stocks.fa.supplier |List of Suppliers |
| Path | Description |
| :---------------------------- | -----------------------------------------------: |
| openbb.stocks.fa.analysis | Analysis of SEC disclosure statements |
| openbb.stocks.fa.balance | Company balance sheet |
| openbb.stocks.fa.cal | Calendar earnings and estimates |
| openbb.stocks.fa.cash | Company cash flows statements |
| openbb.stocks.fa.customer | Lists other public companies who are customers |
| openbb.stocks.fa.dcfc | Historical DCF Values for a ticker |
| openbb.stocks.fa.divs | Historical Dividends for a company |
| openbb.stocks.fa.divs_chart | A chart for `divs` |
| openbb.stocks.fa.dupont | DuPont ratios |
| openbb.stocks.fa.earnings | Earnings data and EPS |
| openbb.stocks.fa.enterprise | Company enterprise value |
| openbb.stocks.fa.epsfc | Forward EPS estimates |
| openbb.stocks.fa.fama_coe | Fama/French value for cost of equity |
| openbb.stocks.fa.fraud | Key fraud ratios |
| openbb.stocks.fa.growth | Growth of financial statement ratios |
| openbb.stocks.fa.income | Company income statements |
| openbb.stocks.fa.key | Company Key Metrics |
| openbb.stocks.fa.metrics | Key Metrics Over Time |
| openbb.stocks.fa.mgmt | Company Management Team |
| openbb.stocks.fa.mktcap | Estimated Market Cap |
| openbb.stocks.fa.mktcap_chart | Chart for `mktcap` |
| openbb.stocks.fa.overview | Overview of the company |
| openbb.stocks.fa.pt | Analyst price targets |
| openbb.stocks.fa.pt_chart | Chart for `pt` |
| openbb.stocks.fa.rating | Historical buy/sell/hold ratings based on ratios |
| openbb.stocks.fa.ratios | Historical financial statements ratios |
| openbb.stocks.fa.revfc | Forward revenue estimates |
| openbb.stocks.fa.score | Investing Score from Warren Buffet |
| openbb.stocks.fa.shrs | Major shareholders |
| openbb.stocks.fa.splits | Stock Splits and Reverse Splits Since IPO |
| openbb.stocks.fa.splits_chart | Chart for `splits` |
| openbb.stocks.fa.supplier | Lists other public companies who are suppliers |
Alternatively the contents of the module can be printed with:
This can be printed to the screen with:
```python
help(openbb.stocks.fa)
```
Parameters for each function are displayed using the same syntax.
```python
help(openbb.stocks.fa.balance)
Signature:
openbb.stocks.fa.balance(
symbol: str,
quarterly: bool = False,
ratios: bool = False,
source: str = 'YahooFinance',
limit: int = 10,
) -> pandas.core.frame.DataFrame
Call signature: openbb.stocks.fa.balance(*args: Any, **kwargs: Any) -> Any
Type: get_balance_sheet
String form: <openbb_terminal.stocks.fundamental_analysis.sdk_helpers.Operation object at 0x1684e8f70>
File: ~/GitHub/OpenBBTerminal/openbb_terminal/stocks/fundamental_analysis/sdk_helpers.py
Docstring:
Get balance sheet.
Parameters
----------
symbol : str
Symbol to get balance sheet for
source : str, optional
Data source for balance sheet, by default "YahooFinance"
Sources: YahooFinance, AlphaVantage, FinancialModelingPrep, Polygon, EODHD
quarterly : bool, optional
Flag to get quarterly data
ratios : bool, optional
Flag to return data as a percent change.
limit : int
Number of statements to return (free tiers may be limited to 5 years)
Returns
-------
pd.DataFrame
Dataframe of balance sheet
Examples
--------
>>> from openbb_terminal.sdk import openbb
>>> balance_sheet = openbb.stocks.fa.balance("AAPL", source="YahooFinance")
If you have a premium AlphaVantage key, you can use the quarterly flag to get quarterly statements
>>> quarterly_income_statement = openbb.stocks.fa.balance("AAPL", source="AlphaVantage", quarterly=True)
```
This information is also displayed in the contextual help window, when using Jupyter Lab or VS Code.
## Examples
The examples provided below will assume that the following import block is included at the beginning of the Python script or Notebook file:
```python
import pandas as pd
from openbb_terminal.sdk import openbb
```
@@ -82,86 +128,59 @@ The `openbb.stocks.fa.earnings` function returns upcoming earnings dates and est
openbb.stocks.fa.earnings('COST', quarterly = True)
```
| | Symbol | Company | Earnings Date | EPS Estimate | Reported EPS | Surprise(%) |
|---:|:---------|:-----------------------------|:-----------------------|---------------:|---------------:|--------------:|
| 0 | COST | Costco Wholesale Corp | Sep 20, 2023, 4 PMEDT | nan | nan | nan |
| 1 | COST | Costco Wholesale Corp | May 24, 2023, 4 PMEDT | nan | nan | nan |
| 2 | COST | Costco Wholesale Corp | Dec 08, 2022, 5 PMEST | 3.11 | nan | nan |
| 3 | COST | Costco Wholesale Corp | Dec 07, 2022, 4 PMEST | 3.11 | nan | nan |
| 4 | COST | Costco Wholesale Corporation | Sep 22, 2022, 12 PMEDT | 4.17 | 4.2 | 0.84 |
| 95 | COST | Costco Wholesale Corporation | Oct 06, 1999, 12 AMEDT | 0.38 | 0.4 | 3.64 |
| 96 | COST | Costco Wholesale Corporation | May 26, 1999, 12 AMEDT | 0.22 | 0.23 | 4.41 |
| 97 | COST | Costco Wholesale Corporation | Mar 04, 1999, 12 AMEST | 0.32 | 0.35 | 8.57 |
| 98 | COST | Costco Wholesale Corporation | Dec 17, 1998, 12 AMEST | 0.23 | 0.23 | 0.9 |
| 99 | COST | Costco Wholesale Corporation | Oct 08, 1998, 12 AMEDT | 0.32 | 0.33 | 1.87 |
| Earnings Date | EPS Estimate | Reported EPS | Surprise(%) |
| :------------ | :----------- | :----------- | :---------- |
| 2024-02-29 | - | - | - |
| 2023-12-06 | - | - | - |
| 2023-09-20 | - | - | - |
| 2023-05-25 | 3.21 | - | - |
| 2023-05-25 | - | - | - |
| 2023-03-02 | 3.21 | 3.3 | 0.0288 |
| 2022-12-08 | 3.11 | 3.1 | -0.00451 |
| 2022-09-22 | 4.17 | 4.2 | 0.0084 |
| 2022-05-26 | 3.03 | 3.17 | 0.0449 |
| 2022-03-03 | 2.74 | 2.92 | 0.0647 |
| 2021-12-09 | 2.64 | 2.98 | 0.12890 |
### Growth
`openbb.stocks.fa.growth` provides annualized financial ratios as growth metrics.
```python
openbb.stocks.fa.growth('COST', limit = 20)
openbb.stocks.fa.growth('COST')
```
| | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 |
|:--------------------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|
| Period | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY | FY |
| Revenue growth | 0.158 | 0.175 | 0.092 | 0.079 | 0.097 | 0.087 | 0.022 | 0.032 | 0.071 | 0.061 | 0.115 | 0.141 | 0.091 | -0.015 | 0.126 | 0.071 | 0.136 | 0.100 | 0.131 | 0.098 |
| Gross profit growth | 0.092 | 0.157 | 0.101 | 0.076 | 0.075 | 0.084 | 0.045 | 0.067 | 0.074 | 0.073 | 0.102 | 0.123 | 0.095 | 0.012 | 0.130 | 0.074 | 0.124 | 0.095 | 0.133 | 0.111 |
| Debt growth | -0.108 | -0.003 | 0.49 | 0.052 | -0.026 | 0.29 | -0.16 | 0.207 | 0.019 | 2.616 | -0.358 | -0.006 | -0.059 | -0.018 | 0.056 | 2.93 | -0.264 | -0.418 | -0.012 | 0.023 |
**Note**: This returns thirty-five ratios, the table below is truncated for illustrative purposes.
| | 2018 | 2019 | 2020 | 2021 | 2022 |
| :---------------------- | :---- | :----- | :---- | :---- | :---- |
| Period | FY | FY | FY | FY | FY |
| Revenue growth | 0.097 | 0.079 | 0.092 | 0.175 | 0.158 |
| Gross profit growth | 0.075 | 0.076 | 0.101 | 0.157 | 0.092 |
| Ebitgrowth | 0.090 | -0.236 | 0.134 | 0.306 | 0.203 |
| Operating income growth | 0.090 | -0.236 | 0.134 | 0.306 | 0.203 |
### Analysis
The `openbb.stocks.fa.analysis` function scans 10K SEC filings with NLP to highlight risk factors and notable statements provided by the company.
The `openbb.stocks.fa.analysis` function scans 10K SEC filings with NLP to highlight risk factors and statements provided in the Discussion and Analysis sections. Summarizations by, [elclect.us](https://eclect.us/)
```python
openbb.stocks.fa.analysis('COST')
openbb.stocks.fa.analysis('COST').head(1)
```
| | Group | Good | Sentence |
|---:|:------------------------|:-------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | Risk factors | False | During 2022, our international operations, including Canada, generated 27% and 32% of our net sales and operating income, respectively. |
| 1 | Risk factors | False | Changes in tax rates, new U. S. or foreign tax legislation, and exposure to additional tax liabilities could adversely affect our financial condition and results of operations. |
| 8 | Risk factors | True | Declines in financial performance of our U. S. operations, particularly in California, and our Canadian operations could arise from, among other things: slow growth or declines in comparable warehouse sales (comparable sales); negative trends in operating expenses, including increased labor, healthcare and energy costs; failing to meet targets for warehouse openings; cannibalizing existing locations with new warehouses; shifts in sales mix toward lower gross margin products; changes or uncertainties in economic conditions in our markets, including higher levels of unemployment and depressed home values; and failing to consistently provide high quality and innovative new products. |
| 26 | Discussion and Analysis | True | Stock Repurchase ProgramsDuring 2022 and 2021, we repurchased 863,000 and 1,358, 000 shares of common stock, at average prices of $511.46 and $364.39, respectively, totaling approximately $442 and $495, respectively. |
### Sust
A company's ESG scores are fetched with:
| Group | Good | Sentence |
| :----------- | :---- | :-------------------------------------------------------------------------------------------------------------------------------------- |
| Risk factors | False | During 2022, our international operations, including Canada, generated 27% and 32% of our net sales and operating income, respectively. |
```python
openbb.stocks.fa.sust('COST')
df = openbb.stocks.fa.analysis('COST')
hp = df["Group"].str.contains('Discussion')
df[hp].head(1)
```
| | Value |
|:-----------------------|:---------------|
| Palm oil | False |
| Controversial weapons | False |
| Gambling | False |
| Social score | 11.21 |
| Nuclear | False |
| Fur leather | False |
| Alcoholic | False |
| Gmo | False |
| Catholic | False |
| Social percentile | |
| Peer count | 33 |
| Governance score | 5.72 |
| Environment percentile | |
| Animal testing | False |
| Tobacco | False |
| Total esg | 24.19 |
| Highest controversy | 3 |
| Esg performance | AVG_PERF |
| Coal | False |
| Pesticides | False |
| Adult | False |
| Percentile | 40.87 |
| Peer group | Food Retailers |
| Small arms | False |
| Environment score | 7.26 |
| Governance percentile | |
| Military contract | False |
| Group | Good | Sentence |
| :---------------------- | :--- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Discussion and Analysis | True | Cash Flows from Operating ActivitiesNet cash provided by operating activities totaled $5,802 in the first half of 2023, compared to $3,659 in the first half of 2022. |
### Key
@@ -172,70 +191,40 @@ openbb.stocks.fa.key('COST')
```
| | |
|:-------------------------|:----------|
| Market capitalization | 238.674 B |
| EBITDA | 9.693 B |
| EPS | 13.14 |
| PE ratio | 41.04 |
| PEG ratio | 3.759 |
| Price to book ratio | 11.34 |
| Return on equity TTM | 0.305 |
| Price to sales ratio TTM | 1.052 |
| Dividend yield | 0.0068 |
| 50 day moving average | 493.34 |
| Analyst target price | 562.93 |
| Beta | 0.717 |
| :----------------------- | :-------- |
| Market capitalization | 219.440 B |
| EBITDA | 9.891 B |
| EPS | 13.62 |
| PE ratio | 36.33 |
| PEG ratio | 3.433 |
| Price to book ratio | 10.39 |
| Return on equity TTM | 0.284 |
| Price to sales ratio TTM | 0.891 |
| Dividend yield | 0.0083 |
| 50 day moving average | 491.41 |
| Analyst target price | 547.64 |
| Beta | 0.787 |
### SHRS
Ownership metrics for a company are listed with:
```python
openbb.stocks.fa.shrs(symbol = 'COST', holder = 'major')
```
| | | |
|---:|:-------|:------------------------------------------|
| 0 | 0.22% | Percentage of Shares Held by All Insider |
| 1 | 69.05% | Percentage of Shares Held by Institutions |
| 2 | 69.21% | Percentage of Float Held by Institutions |
| 3 | 3444 | Number of Institutions Holding Shares |
Accepted arguments for `holder` are `major`, `mutualfund`, and `institutional`.
The top 10 mutual funds holding the stock are retrieved with:
```python
openbb.stocks.fa.shrs(symbol = 'COST', holder = 'mutualfund')
```
| | Holder | Shares | Date Reported | Stake | Value |
|---:|:-----------------------------------------------------------|:---------|:--------------------|:--------|:--------|
| 0 | Vanguard Total Stock Market Index Fund | 13.051 M | 2022-06-29 00:00:00 | 2.95 % | 6.576 B |
| 1 | Vanguard 500 Index Fund | 10.041 M | 2022-09-29 00:00:00 | 2.27 % | 5.059 B |
| 2 | Invesco ETF Tr-Invesco QQQ Tr, Series 1 ETF | 6.504 M | 2022-09-29 00:00:00 | 1.47 % | 3.277 B |
| 3 | SPDR S&P 500 ETF Trust | 5.062 M | 2022-10-30 00:00:00 | 1.14 % | 2.551 B |
| 4 | Fidelity 500 Index Fund | 4.785 M | 2022-09-29 00:00:00 | 1.08 % | 2.411 B |
| 5 | iShares Core S&P 500 ETF | 3.938 M | 2022-09-29 00:00:00 | 0.89 % | 1.984 B |
| 6 | Vanguard Growth Index Fund | 3.648 M | 2022-09-29 00:00:00 | 0.82 % | 1.838 B |
| 7 | Vanguard Institutional Index Fund-Institutional Index Fund | 3.216 M | 2022-09-29 00:00:00 | 0.73 % | 1.621 B |
| 8 | Select Sector SPDR Fund-Consumer Staples | 3.131 M | 2022-10-30 00:00:00 | 0.71 % | 1.577 B |
| 9 | Vanguard Specialized-Dividend Appreciation Index Fund | 2.740 M | 2022-07-30 00:00:00 | 0.62 % | 1.380 B |
```python
openbb.stocks.fa.shrs(symbol = 'COST', holder = 'institutional')
```
| | Holder | Shares | Date Reported | Stake | Value |
|---:|:------------------------------------|:---------|:--------------------|:--------|:---------|
| 0 | Vanguard Group, Inc. (The) | 39.030 M | 2022-09-29 00:00:00 | 8.82 % | 19.666 B |
| 1 | Blackrock Inc. | 30.060 M | 2022-09-29 00:00:00 | 6.79 % | 15.146 B |
| 2 | State Street Corporation | 18.802 M | 2022-09-29 00:00:00 | 4.25 % | 9.473 B |
| 3 | FMR, LLC | 10.346 M | 2022-09-29 00:00:00 | 2.34 % | 5.213 B |
| 4 | Geode Capital Management, LLC | 8.044 M | 2022-09-29 00:00:00 | 1.82 % | 4.053 B |
| 5 | Bank of America Corporation | 7.875 M | 2022-09-29 00:00:00 | 1.78 % | 3.968 B |
| 6 | Morgan Stanley | 7.319 M | 2022-09-29 00:00:00 | 1.65 % | 3.688 B |
| 7 | Northern Trust Corporation | 4.976 M | 2022-09-29 00:00:00 | 1.12 % | 2.507 B |
| 8 | AllianceBernstein, L.P. | 4.680 M | 2022-09-29 00:00:00 | 1.06 % | 2.358 B |
| 9 | Bank Of New York Mellon Corporation | 4.481 M | 2022-09-29 00:00:00 | 1.01 % | 2.258 B |
| Holder | Shares | Date Reported | Stake | Value |
| :--------------------------------------------------------- | :------- | :------------------ | :----- | :------ |
| Vanguard Total Stock Market Index Fund | 13.453 M | 2022-12-30 00:00:00 | 3.03 % | 6.591 B |
| Vanguard 500 Index Fund | 10.232 M | 2022-12-30 00:00:00 | 2.31 % | 5.012 B |
| Invesco ETF Tr-Invesco QQQ Tr, Series 1 ETF | 5.834 M | 2023-03-30 00:00:00 | 1.32 % | 2.858 B |
| Fidelity 500 Index Fund | 4.852 M | 2023-02-27 00:00:00 | 1.09 % | 2.377 B |
| SPDR S&P 500 ETF Trust | 4.804 M | 2023-03-30 00:00:00 | 1.08 % | 2.353 B |
| iShares Core S&P 500 ETF | 3.950 M | 2023-02-27 00:00:00 | 0.89 % | 1.935 B |
| Vanguard Growth Index Fund | 3.736 M | 2022-12-30 00:00:00 | 0.84 % | 1.830 B |
| Select Sector SPDR Fund-Consumer Staples | 3.241 M | 2023-02-27 00:00:00 | 0.73 % | 1.588 B |
| Vanguard Institutional Index Fund-Institutional Index Fund | 3.102 M | 2022-12-30 00:00:00 | 0.70 % | 1.519 B |
| Vanguard Specialized-Dividend Appreciation Index Fund | 2.804 M | 2023-01-30 00:00:00 | 0.63 % | 1.374 B |
### Balance
@@ -245,285 +234,138 @@ Financial statement items can be displayed as their reported value or as a perce
openbb.stocks.fa.balance(symbol = 'COST', ratios=True)
```
| Breakdown | 2022-08-31 | 2021-08-31 | 2020-08-31 |
|:-------------------------------------------|-------------:|-------------:|-------------:|
| Cash and cash equivalents | -0.0937111 | -0.0830007 | 0.464337 |
| Other short-term investments | -0.0774264 | -0.107977 | -0.0301887 |
| Total cash | -0.0924846 | -0.0849305 | 0.408831 |
| Net receivables | 0.242928 | 0.163226 | 0.00977199 |
| Inventory | 0.259726 | 0.161166 | 0.0743308 |
| Other current assets | 0.14253 | 0.282502 | -0.0792079 |
| Total current assets | 0.108151 | 0.0492532 | 0.19736 |
| Gross property, plant and equipment | 0.0532209 | 0.0815396 | 0.149114 |
| Accumulated depreciation | 0.0790625 | 0.0984801 | 0.0988412 |
| Net property, plant and equipment | 0.039345 | 0.072657 | 0.177358 |
| Other long-term assets | 0.19787 | 0.190074 | 1.77171 |
| Total non-current assets | 0.0573531 | 0.0848156 | 0.251928 |
| Total assets | 0.0826416 | 0.0668155 | 0.2237 |
| Current debt | -0.908636 | 7.41053 | -0.944085 |
| Accounts payable | 0.0964492 | 0.148603 | 0.21346 |
| Accrued liabilities | 0.0921715 | 0.152661 | 0.147383 |
| Other current liabilities | 0.230213 | 0.223444 | -0.0168776 |
| Total current liabilities | 0.0868517 | 0.185035 | 0.0691569 |
| Long-term debt | -0.0310819 | -0.109396 | 0.466432 |
| Other long-term liabilities | 0.057971 | 0.248062 | 0.329897 |
| Total non-current liabilities | -0.0194059 | -0.0214875 | 0.825049 |
| Total liabilities | 0.0565429 | 0.117744 | 0.235947 |
| Common stock | -0.5 | 0 | 0 |
| Retained earnings | 0.335933 | -0.0941843 | 0.255508 |
| Accumulated other comprehensive income | 0.608619 | -0.123362 | -0.0967967 |
| Total stockholders' equity | 0.175245 | -0.0393787 | 0.199501 |
| Total liabilities and stockholders' equity | 0.0826416 | 0.0668155 | 0.2237 |
| Breakdown | 2022-08-31 | 2021-08-31 | 2020-08-31 |
| :----------------------------------------- | ---------: | ---------: | ---------: |
| Cash and cash equivalents | -0.0937111 | -0.0830007 | 0.464337 |
| Other short-term investments | -0.0774264 | -0.107977 | -0.0301887 |
| Total cash | -0.0924846 | -0.0849305 | 0.408831 |
| Net receivables | 0.242928 | 0.163226 | 0.00977199 |
| Inventory | 0.259726 | 0.161166 | 0.0743308 |
| Other current assets | 0.14253 | 0.282502 | -0.0792079 |
| Total current assets | 0.108151 | 0.0492532 | 0.19736 |
| Gross property, plant and equipment | 0.0532209 | 0.0815396 | 0.149114 |
| Accumulated depreciation | 0.0790625 | 0.0984801 | 0.0988412 |
| Net property, plant and equipment | 0.039345 | 0.072657 | 0.177358 |
| Other long-term assets | 0.19787 | 0.190074 | 1.77171 |
| Total non-current assets | 0.0573531 | 0.0848156 | 0.251928 |
| Total assets | 0.0826416 | 0.0668155 | 0.2237 |
| Current debt | -0.908636 | 7.41053 | -0.944085 |
| Accounts payable | 0.0964492 | 0.148603 | 0.21346 |
| Accrued liabilities | 0.0921715 | 0.152661 | 0.147383 |
| Other current liabilities | 0.230213 | 0.223444 | -0.0168776 |
| Total current liabilities | 0.0868517 | 0.185035 | 0.0691569 |
| Long-term debt | -0.0310819 | -0.109396 | 0.466432 |
| Other long-term liabilities | 0.057971 | 0.248062 | 0.329897 |
| Total non-current liabilities | -0.0194059 | -0.0214875 | 0.825049 |
| Total liabilities | 0.0565429 | 0.117744 | 0.235947 |
| Common stock | -0.5 | 0 | 0 |
| Retained earnings | 0.335933 | -0.0941843 | 0.255508 |
| Accumulated other comprehensive income | 0.608619 | -0.123362 | -0.0967967 |
| Total stockholders' equity | 0.175245 | -0.0393787 | 0.199501 |
| Total liabilities and stockholders' equity | 0.0826416 | 0.0668155 | 0.2237 |
Cashflow and Income statements function in the same way as `balance` does.
Cashflow and Income statements are requested in the same way.
### Cash
Get the company's cash statements.
```python
openbb.stocks.fa.cash(symbol = 'COST')
openbb.stocks.fa.cash(symbol = 'COST').tail(4)
```
| Breakdown | ttm | 2022-08-31 | 2021-08-31 | 2020-08-31 | 2019-08-31 |
|:----------------------------------------------------------|------------:|-------------:|-------------:|-------------:|:-------------|
| Net income | 5844000000 | 5844000000 | 5007000000 | 4002000000 | 3659000000 |
| Depreciation & amortisation | 1900000000 | 1900000000 | 1781000000 | 1645000000 | 1492000000 |
| Deferred income taxes | -37000000 | -37000000 | 59000000 | 104000000 | 147000000 |
| Stock-based compensation | 724000000 | 724000000 | 665000000 | 619000000 | 595000000 |
| Change in working capital | -1563000000 | -1563000000 | 1003000000 | 2198000000 | 409000000 |
| Inventory | -4003000000 | -4003000000 | -1892000000 | -791000000 | -536000000 |
| Accounts payable | 1891000000 | 1891000000 | 1838000000 | 2261000000 | 322000000 |
| Other working capital | 3501000000 | 3501000000 | 5370000000 | 6051000000 | 3358000000 |
| Other non-cash items | 453000000 | 453000000 | 371000000 | 236000000 | 9000000 |
| Net cash provided by operating activities | 7392000000 | 7392000000 | 8958000000 | 8861000000 | 6356000000 |
| Investments in property, plant and equipment | -3891000000 | -3891000000 | -3588000000 | -2810000000 | -2998000000 |
| Acquisitions, net | 0 | 0 | 0 | -1163000000 | `<NA>` |
| Purchases of investments | -1121000000 | -1121000000 | -1331000000 | -1626000000 | -1094000000 |
| Sales/maturities of investments | 1145000000 | 1145000000 | 1446000000 | 1678000000 | 1231000000 |
| Other investing activities | -48000000 | -48000000 | -62000000 | 30000000 | -4000000 |
| Net cash used for investing activities | -3915000000 | -3915000000 | -3535000000 | -3891000000 | -2865000000 |
| Debt repayment | -800000000 | -800000000 | -94000000 | -3200000000 | -89000000 |
| Common stock repurchased | -439000000 | -439000000 | -496000000 | -196000000 | -247000000 |
| Dividends paid | -1498000000 | -1498000000 | -5748000000 | -1479000000 | -1038000000 |
| Other financing activities | -1546000000 | -1546000000 | -379000000 | -401000000 | -281000000 |
| Net cash used provided by (used for) financing activities | -4283000000 | -4283000000 | -6488000000 | -1147000000 | -1147000000 |
| Net change in cash | -1055000000 | -1055000000 | -1019000000 | 3893000000 | 2329000000 |
| Cash at beginning of period | 11258000000 | 11258000000 | 12277000000 | 8384000000 | 6055000000 |
| Cash at end of period | 10203000000 | 10203000000 | 11258000000 | 12277000000 | 8384000000 |
| Operating cash flow | 7392000000 | 7392000000 | 8958000000 | 8861000000 | 6356000000 |
| Capital expenditure | -3891000000 | -3891000000 | -3588000000 | -2810000000 | -2998000000 |
| Free cash flow | 3501000000 | 3501000000 | 5370000000 | 6051000000 | 3358000000 |
| Breakdown | ttm | 2022-08-31 | 2021-08-31 | 2020-08-31 | 2019-08-31 |
| :-------------------- | ---------: | ---------: | ---------: | ---------: | ---------: |
| Cash at end of period | 13136000.0 | 10203000.0 | 11258000.0 | 12277000.0 | 8384000.0 |
| Operating cash flow | 9535000.0 | 7392000.0 | 8958000.0 | 8861000.0 | 6356000.0 |
| Capital expenditure | -4060000.0 | -3891000.0 | -3588000.0 | -2810000.0 | -2998000.0 |
| Free cash flow | 5475000.0 | 3501000.0 | 5370000.0 | 6051000.0 | 3358000.0 |
### Income
Get the company's income statements.
```python
openbb.stocks.fa.income('COST')
openbb.stocks.fa.income('COST').tail(4)
```
| Breakdown | ttm | 2022-08-31 | 2021-08-31 | 2020-08-31 | 2019-08-31 |
|:----------------------------------------------------------|------------:|-------------:|-------------:|-------------:|:-------------|
| Net income | 5844000000 | 5844000000 | 5007000000 | 4002000000 | 3659000000 |
| Depreciation & amortisation | 1900000000 | 1900000000 | 1781000000 | 1645000000 | 1492000000 |
| Deferred income taxes | -37000000 | -37000000 | 59000000 | 104000000 | 147000000 |
| Stock-based compensation | 724000000 | 724000000 | 665000000 | 619000000 | 595000000 |
| Change in working capital | -1563000000 | -1563000000 | 1003000000 | 2198000000 | 409000000 |
| Inventory | -4003000000 | -4003000000 | -1892000000 | -791000000 | -536000000 |
| Accounts payable | 1891000000 | 1891000000 | 1838000000 | 2261000000 | 322000000 |
| Other working capital | 3501000000 | 3501000000 | 5370000000 | 6051000000 | 3358000000 |
| Other non-cash items | 453000000 | 453000000 | 371000000 | 236000000 | 9000000 |
| Net cash provided by operating activities | 7392000000 | 7392000000 | 8958000000 | 8861000000 | 6356000000 |
| Investments in property, plant and equipment | -3891000000 | -3891000000 | -3588000000 | -2810000000 | -2998000000 |
| Acquisitions, net | 0 | 0 | 0 | -1163000000 | `<NA>` |
| Purchases of investments | -1121000000 | -1121000000 | -1331000000 | -1626000000 | -1094000000 |
| Sales/maturities of investments | 1145000000 | 1145000000 | 1446000000 | 1678000000 | 1231000000 |
| Other investing activities | -48000000 | -48000000 | -62000000 | 30000000 | -4000000 |
| Net cash used for investing activities | -3915000000 | -3915000000 | -3535000000 | -3891000000 | -2865000000 |
| Debt repayment | -800000000 | -800000000 | -94000000 | -3200000000 | -89000000 |
| Common stock repurchased | -439000000 | -439000000 | -496000000 | -196000000 | -247000000 |
| Dividends paid | -1498000000 | -1498000000 | -5748000000 | -1479000000 | -1038000000 |
| Other financing activities | -1546000000 | -1546000000 | -379000000 | -401000000 | -281000000 |
| Net cash used provided by (used for) financing activities | -4283000000 | -4283000000 | -6488000000 | -1147000000 | -1147000000 |
| Net change in cash | -1055000000 | -1055000000 | -1019000000 | 3893000000 | 2329000000 |
| Cash at beginning of period | 11258000000 | 11258000000 | 12277000000 | 8384000000 | 6055000000 |
| Cash at end of period | 10203000000 | 10203000000 | 11258000000 | 12277000000 | 8384000000 |
| Operating cash flow | 7392000000 | 7392000000 | 8958000000 | 8861000000 | 6356000000 |
| Capital expenditure | -3891000000 | -3891000000 | -3588000000 | -2810000000 | -2998000000 |
| Free cash flow | 3501000000 | 3501000000 | 5370000000 | 6051000000 | 3358000000 |
### Customer
`openbb.stocks.fa.customer` returns a table of a company's publicly-listed customers and their changes in revenue and income.
```python
gtlb_customers = openbb.stocks.fa.customer('GTLB')
gtlb_customers
```
| TICKER | Company Name | Rev. Y/Y | Rev. Seq. | Inc. Y/Y | Inc. Seq. |
|:---------|:-----------------------------|:-------------|:-------------|:-----------|:------------|
| GTLB | Gitlab Inc. | - | 15.6 % | - | - |
| TICKER | CUSTOMER NAME | COST OF REV. | COST OF REV. | SG&A | SG&A |
| ALRM | Alarm com Holdings Inc | 6.47 % | -2 % | -44.1 % | -55.87 % |
| YOU | Clear Secure Inc | - | - | - | -82.32 % |
| EFX | Equifax Inc | 10.94 % | 0.07 % | -7.61 % | -3.69 % |
| EVBG | Everbridge Inc | 16.95 % | 6.64 % | -25.27 % | -35.71 % |
| EVCM | Evercommerce Inc | 34.21 % | 4.63 % | -42.2 % | -53.49 % |
| RSKIA | George Risk Industries Inc. | 14.62 % | -5.51 % | -2.11 % | -3.44 % |
| INFY | Infosys Limited | 24.56 % | - | - | - |
| XM | Qualtrics International Inc | 67.05 % | 6.91 % | -43.49 % | -44.79 % |
| SEM | Select Medical Holdings Corp | 7.41 % | 0.23 % | 4.24 % | 5.96 % |
| CXM | Sprinklr Inc. | 12.91 % | 1.05 % | 15.26 % | 1.01 % |
| SPT | Sprout Social Inc | 24.02 % | 1.14 % | -1.88 % | -28.69 % |
| TRU | Transunion | - | - | 34.9 % | 1.99 % |
| Breakdown | 2022-08-31 | 2021-08-31 | 2020-08-31 | 2019-08-31 |
| :--------------------- | :--------: | :--------: | :--------: | ---------: |
| Diluted EPS | 13.14 | 11.27 | 9.02 | 8.26 |
| Basic average shares | 443651.00 | 443089.00 | 442297.00 | 439755.00 |
| Diluted average shares | 444757.00 | 444346.00 | 443901.00 | 442923.00 |
| EBITDA | 7998000.00 | 6851000.00 | 5527000.00 | 4915000.00 |
### Supplier
`openbb.stocks.fa.supplier` is the supply side to the `customer` function. It returns revenue, net income, net margin, and cash flow, for the companies feeding the ticker's supply chain.
`openbb.stocks.fa.supplier` will return a list of suppliers for the compnay, that are also listed US stocks.
```python
gtlb_suppliers = openbb.stocks.fa.supplier('GTLB')
gtlb_suppliers
openbb.stocks.fa.supplier('COST').head(5)
```
| TICKER | Company Name | Revenue | Net Income | Net Margin | Cash Flow |
|:---------|:--------------------------------------------|----------:|-------------:|:-------------|------------:|
| MSFT | Microsoft Corporation | 50122 | 17556 | 35.03 % | 8953 |
| DELL | Dell Technologies Inc. | 26425 | 506 | 1.91 % | -1183 |
| ORCL | Oracle Corporation | 21529 | 1548 | 7.19 % | -10935 |
| HPQ | Hp Inc. | 14664 | 1119 | 7.63 % | 909 |
| IBM | International Business Machines Corporation | 14107 | -3196 | - | 721 |
| CSCO | Cisco Systems Inc | 13632 | 2670 | 19.59 % | 213 |
| NCR | Ncr Corp | 1972 | 69 | 3.5 % | 81 |
| FFIV | F5 Inc | 700.03 | 89.35 | 12.76 % | 218.82 |
| PTC | Ptc Inc | 507.93 | 106.84 | 21.03 % | -50.16 |
| CGNT | Cognyte Software Ltd | 474.04 | -10.26 | - | 43.56 |
| UIS | Unisys Corp | 461.2 | -39.9 | - | -24.3 |
| NTNX | Nutanix Inc. | 385.54 | -150.99 | - | 16.08 |
| ZS | Zscaler Inc. | 372.17 | -129.99 | - | 418.32 |
| PAYC | Paycom Software Inc | 334.17 | 52.15 | 15.61 % | -1618.67 |
| CDAY | Ceridian Hcm Holding Inc | 315.6 | -21 | - | -959.6 |
| TUYA | Tuya Inc | 302.08 | -175.42 | - | 805.62 |
| NET | Cloudflare Inc | 253.86 | -42.55 | - | -4.76 |
| PCTY | Paylocity Holding Corporation | 253.28 | 30.35 | 11.98 % | -1836.35 |
| ZI | Zoominfo Technologies Inc | 251.7 | 17.9 | 7.11 % | 53.9 |
| PATH | Uipath Inc. | 242.22 | -120.38 | - | -71.86 |
| BL | Blackline Inc | 134.27 | -18.99 | - | -17.95 |
| WK | Workiva Inc | 132.85 | -29.69 | - | 80.07 |
| PYCR | Paycor Hcm Inc | 118.3 | -29.05 | - | -915.72 |
| APPN | Appian Corporation | 117.88 | -44 | - | -25.24 |
| AVID | Avid Technology Inc | 102.99 | 12.02 | 11.67 % | -13.12 |
| GTLB | Gitlab Inc. | 101.04 | -61.5 | - | -476.73 |
| ATTU | Attunity Ltd | 86.25 | 5.96 | 6.91 % | -17.32 |
| ESMT | Engagesmart Inc | 78.8 | 6.77 | 8.59 % | 19.25 |
| FROG | Jfrog Ltd | 71.99 | -23.55 | - | -1.24 |
| DWCH | Datawatch Corp | 11.59 | -2.27 | - | 0.15 |
| GSB | Globalscape Inc | 10.03 | 3.5 | 34.9 % | 3.17 |
| STVVY | China Digital Tv Holding Co., Ltd. | 6.2 | -4.1 | - | -92.87 |
| FALC | Falconstor Software Inc | 3.06 | 0.6 | 19.64 % | -0.14 |
| ZRFY | Zerify Inc | 0.02 | -1.25 | - | -0.32 |
| TICKER | Company Name | Revenue | Net Income | Net Margin | Cash Flow |
| :----- | :---------------------- | ------: | ---------: | :--------- | --------: |
| BRKA | Berkshire Hathaway Inc | 78165 | 18321 | 23.44 % | -52307 |
| ULVR | Unilever Plc | 58737.3 | 7415.52 | 12.62 % | 0 |
| COST | Costco Wholesale Corp | 54437 | 1364 | 2.51 % | 653 |
| BUD | Anheuser busch Inbev Sa | 54304 | 6114 | 11.26 % | 0 |
| DEO | Diageo Plc | 22448 | 3338 | 14.87 % | 2749 |
### ROT
### EPSFC
`openbb.stocks.fa.rot` returns a table with the number of analyst recommendations for each score, updated monthly.
Returns a DataFrame of forward EPS estimates consensus.
```python
gtlb_rot = openbb.stocks.fa.rot('GTLB')
gtlb_rot
openbb.stocks.fa.epsfc('COST')
```
| | buy | hold | period | sell | strongBuy | strongSell | symbol |
|---:|------:|-------:|:-----------|-------:|------------:|-------------:|:---------|
| 0 | 14 | 2 | 2022-11-01 | 0 | 4 | 0 | GTLB |
| 1 | 14 | 2 | 2022-10-01 | 0 | 4 | 0 | GTLB |
| 2 | 13 | 1 | 2022-09-01 | 0 | 4 | 0 | GTLB |
| 3 | 13 | 1 | 2022-08-01 | 0 | 4 | 0 | GTLB |
### Analyst
Returns a DataFrame of analyst price targets, and their coverage history.
```python
gtlb_pt = openbb.stocks.fa.analyst('GTLB')
gtlb_pt
```
| date | category | analyst | rating | target | target_from | target_to |
|:-----------|:-----------|:-----------------|:----------------------|---------:|--------------:|------------:|
| 2022-09-22 | Initiated | MoffettNathanson | Buy | 104 | nan | nan |
| 2022-09-01 | Downgrade | JP Morgan | Overweight -> Neutral | 63 | nan | nan |
| 2022-07-07 | Initiated | Needham | Buy | 70 | nan | nan |
| 2022-06-27 | Upgrade | Goldman | Neutral -> Buy | nan | 69 | 80 |
| 2022-06-09 | Initiated | Scotiabank | Sector Outperform | 62 | nan | nan |
| fiscalyear | consensus_mean | change % | analysts | actual | consensus_low | consensus_high |
|-------------:|-----------------:|-----------:|-----------:|---------:|----------------:|-----------------:|
| 2022 | 13.151 | 18.6918 | 20 | 13.27 | 12.43 | 13.43 |
| 2023 | 14.5 | 9.2679 | 13 | 0 | 14.22 | 15.18 |
| 2024 | 15.801 | 8.97478 | 20 | 0 | 14.75 | 17.09 |
| 2025 | 17.337 | 9.71807 | 10 | 0 | 16.47 | 18.92 |
| 2026 | 19.332 | 11.5088 | 5 | 0 | 17.55 | 21.84 |
| 2027 | 21.408 | 10.7387 | 5 | 0 | 18.6 | 25.72 |
| 2028 | 23.625 | 10.3559 | 2 | 0 | 22.19 | 25.06 |
| 2029 | 27.2 | 15.1323 | 1 | 0 | 27.2 | 27.2 |
| 2030 | 29.6 | 8.82353 | 1 | 0 | 29.6 | 29.6 |
| 2031 | 32.05 | 8.27703 | 1 | 0 | 32.05 | 32.05 |
| 2032 | 34.87 | 8.79875 | 1 | 0 | 34.87 | 34.87 |
### SEC
`openbb.stocks.fa.sec` gets a DataFrame of the recent SEC filings submitted by the company and a link to view each one.
`openbb.stocks.fa.sec` SEC forms filed by year and type.
```python
gtlb_sec = openbb.stocks.fa.sec('GTLB')
gtlb_sec
openbb.stocks.fa.sec('COST').head(4)
```
| Filing Date | Document Date | Type | Category | Amended | Link |
|:--------------|:----------------|:---------|:------------------------|:----------|:--------------------------------------------------------------------------------------|
| 09/07/2022 | 07/31/2022 | 10-Q | Quarterly Reports | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=16067993 |
| 09/06/2022 | 09/06/2022 | 8-K | Special Events | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=16066715 |
| 07/08/2022 | N/A | SC 13G/A | Institutional Ownership | * | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15940277 |
| 06/23/2022 | 06/17/2022 | 8-K | Special Events | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15906497 |
| 06/07/2022 | 04/30/2022 | 10-Q | Quarterly Reports | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15877097 |
| 06/06/2022 | 06/06/2022 | 8-K | Special Events | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15875737 |
| 05/13/2022 | N/A | SC 13G | Institutional Ownership | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15814288 |
| 05/05/2022 | 01/31/2022 | DEF 14A | Proxy Statement | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15792144 |
| 04/11/2022 | N/A | SC 13G/A | Institutional Ownership | * | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15724191 |
| 04/11/2022 | N/A | S-8 | Registration Statement | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15723998 |
| 04/08/2022 | 01/31/2022 | 10-K | Annual Reports | | https://www.marketwatch.com/investing/stock/gtlb/financials/secfilings?docid=15723401 |
continued...
|Filed |Company Name |Reporting Owner |Form Type |Period |View |
|:-----------|:--------------------------|:------------|:------------|:-----------|:-----------|
|04/19/2023 |Costco Wholesale Corporation | |8-K |04/19/2023 |https://app.quotemedia.com/data/downloadFiling...|
|04/13/2023 |Costco Wholesale Corporation | |4 |04/11/2023 |https://app.quotemedia.com/data/downloadFiling...|
|03/15/2023 |Costco Wholesale Corporation |JELINEK W CRAIG |4 |03/13/2022 |https://app.quotemedia.com/data/downloadFiling...|
|03/15/2023 |Costco Wholesale Corporation |GALANTI RICHARD A |4 |03/14/2023 |https://app.quotemedia.com/data/downloadFiling...|
### EST
### PT
`openbb.stocks.fa.est` returns a Tuple with forward earnings and revenue estimates.
`openbb.stocks.fa.pt` returns historical ratings and price targets, by firm.
```python
year_estimates_df,qtr_earnings_df,qtr_revenue_df = openbb.stocks.fa.est('GTLB')
year_estimates_df
openbb.stocks.fa.pt('COST').tail(10)
```
| YEARLY ESTIMATES | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 |
|:-------------------------------|:-------|:-------|:-------|:--------|:----------|:-------|
| Revenue | 245 | 414 | 586 | 814 | 1,044 | 1,305 |
| Dividend | 0.00 | - | 0.00 | 0.00 | - | - |
| Dividend Yield (in %) | - | - | - | - | - | - |
| EPS | -1.40 | -0.65 | -0.65 | -0.35 | -0.02 | 0.27 |
| P/E Ratio | -28.07 | -60.24 | -60.97 | -113.57 | -1,970.00 | 145.93 |
| EBIT | -103 | -109 | -101 | -62 | -17 | 30 |
| EBITDA | -99 | -123 | -124 | -51 | -10 | 40 |
| Net Profit | -152 | -151 | -177 | -100 | -4 | 50 |
| Net Profit Adjusted | -114 | -98 | -99 | -55 | -4 | 51 |
| Pre-Tax Profit | -121 | -100 | -96 | -53 | -4 | 48 |
| Net Profit (Adjusted) | -134 | -198 | -218 | -70 | - | - |
| EPS (Non-GAAP) ex. SOE | -1.55 | -0.65 | -0.63 | -0.48 | - | - |
| EPS (GAAP) | -1.90 | -1.34 | -1.56 | -1.20 | - | - |
| Gross Income | 217 | 368 | 509 | 692 | 911 | 1,134 |
| Cash Flow from Investing | -100 | -486 | -9 | -12 | -14 | -17 |
| Cash Flow from Operations | -75 | -67 | -31 | 28 | 120 | 251 |
| Cash Flow from Financing | 561 | 80 | 8 | 0 | - | - |
| Cash Flow per Share | -1.06 | -0.52 | -0.23 | -0.08 | - | - |
| Free Cash Flow | -73 | -77 | -39 | 37 | 106 | 234 |
| Free Cash Flow per Share | -0.96 | -0.56 | -0.22 | - | - | - |
| Book Value per Share | 7.16 | 5.11 | 4.52 | 4.10 | - | - |
| Net Debt | -798 | -403 | -372 | -460 | - | - |
| Research & Development Exp. | 90 | 120 | 158 | 208 | 244 | 292 |
| Capital Expenditure | 0 | 6 | 8 | 13 | - | - |
| Selling, General & Admin. Exp. | 230 | 361 | 473 | 509 | - | - |
| Shareholder’s Equity | 831 | 729 | 649 | 611 | 589 | 639 |
| Total Assets | 1,093 | 1,105 | 1,159 | 1,397 | 1,658 | 2,027 |
| Date | Company | Rating | Price Target |
|:------------|:-----------------------|:---------|---------------:|
| 2023-02-08 | Barclays Capital | HOLD | 510 |
| 2023-02-27 | Telsey Advisory Group | BUY | 580 |
| 2023-03-03 | Baird Patrick & Co | BUY | 535 |
| 2023-03-03 | Telsey Advisory Group | BUY | 540 |
| 2023-03-03 | Morgan Stanley | BUY | 520 |
| 2023-03-07 | Northcoast | BUY | 560 |
| 2023-03-28 | Telsey Advisory Group | BUY | 540 |
| 2023-04-06 | Telsey Advisory Group | BUY | 540 |
| 2023-04-06 | Oppenheimer & Co. Inc. | BUY | 550 |
| 2023-05-01 | Telsey Advisory Group | BUY | 540 |

434
website/content/terminal/usage/intros/economy.md vendored
View File

@@ -1,363 +1,155 @@
---
title: Economy
keywords: [economy, macro, index, treasury, fred, market, econdb, index, yield, curve, economic, indicators, micro, inflation, interest rate, interest, unemployment, gdp, gross domestic product, openbb terminal, how to, example, overview, futures, econdb, fred, yahoo finance, macro, index, forecasting, quantitative]
description: A brief guide to the Economy menu. It includes an introduction to the commands, functionality, data, and in context examples.
description: A brief guide to the Economy menu. It includes an introduction to the commands, functionality, data, and provides examples for use.
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="Economny - Terminal | OpenBB Docs" />
`<HeadTitle title="Economny - Terminal | OpenBB Docs" />`
The Economy menu enables you to obtain market overviews (<a href="/terminal/reference/economy/overview" target="_blank" rel="noreferrer noopener">overview</a> and <a href="/terminal/reference/economy/futures" target="_blank" rel="noreferrer noopener">futures</a>), see yield curves of any country (<a href="/terminal/reference/economy/ycrv" target="_blank" rel="noreferrer noopener">ycrv</a>) and discover sector, industry and country performance (<a href="/terminal/reference/economy/performance" target="_blank" rel="noreferrer noopener">performance</a>). Next to that, the databases of <a href="https://www.econdb.com/" target="_blank" rel="noreferrer noopener">EconDB</a>, <a href="https://fred.stlouisfed.org/" target="_blank" rel="noreferrer noopener">FRED</a> and <a href="https://finance.yahoo.com/" target="_blank" rel="noreferrer noopener">Yahoo Finance</a> can be accessed via <a href="/terminal/reference/economy/macro" target="_blank" rel="noreferrer noopener">macro</a>, <a href="/terminal/reference/economy/fred" target="_blank" rel="noreferrer noopener">fred</a> and <a href="/terminal/reference/economy/index_cmd" target="_blank" rel="noreferrer noopener">index</a> respectively. All of this can also be further analysed with <a href="/terminal/usage/intros/forecast" target="_blank" rel="noreferrer noopener">Forecasting menu</a> (`forecast`) and <a href="/terminal/usage/intros/common/qa" target="_blank" rel="noreferrer noopener">Quantitative Techniques</a> (`qa`).
## Overview
## How to use
The `/economy` menu provides methods for querying macroeconomic data sets from sources like FRED, OECD, and EconDB. To get the most out of this menu, sign up for a free API key from the [Federal Reserve of St. Louis](https://fred.stlouisfed.org/), and enter it into the OpenBB Terminal from the [`/keys` menu](https://docs.openbb.co/terminal/usage/guides/api-keys).
The Economy menu is called upon by typing `economy` which opens the following menu:
## The Economy Menu
<img width="800" alt="image" src="https://user-images.githubusercontent.com/46355364/218990930-84338dbb-64eb-4243-82ff-8d0423f7066c.png"></img>
The menu is divided into four general sections:
Within the Economy menu you have a variety of options ranging from treasury rates to population growth to country financial performance. As this is quite extensive, the guide has two sections. The first section will discuss valuations and performance and the second section discusses the databases.
- **Broad market**: General headline statistics from the markets today.
- **Country performance**: Country-specific data published by the OECD.
- **Databases**: Query time series.
- **Stored datasets**: Compare and chart multiple time series together.
### Performance and valuations
Each command is listed below, with a short description.
By using <a href="/terminal/reference/economy/overview" target="_blank" rel="noreferrer noopener">overview</a> we can look into market overviews from the perspective of indices (`indices`), bonds (`usbonds` and `glbonds`), currencies (`currencies`) and in general. E.g. let's look at global bond performance by adding the `-t` argument:
### Broad Market
```
(🦋) /economy/ $ overview -t glbonds
|Function Key |Description |
|:-----|-----:|
|overview |Market overview of either indices, bonds or currencies. |
|futures |Futures and commodities overview. |
|map |S&P 500 heat map. |
|bigmac |The Economist's Big Mac Index. |
|events |The economic calendar. |
|edebt |External debt statitistics for various countries. |
Global Bonds
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ ┃ Rate (%) ┃ Yld (%) ┃ Yld Chg (%) ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━┩
│ U.S. 10 Year Treasury Note │ 2.875 │ 3.164 │ -0.016 │
├───────────────────────────────────┼──────────┼─────────┼─────────────┤
│ Germany 10 Year Government Bond │ 0.000 │ 1.582 │ -0.046 │
├───────────────────────────────────┼──────────┼─────────┼─────────────┤
│ U.K. 10 Year Gilt │ 4.250 │ 2.440 │ -0.028 │
├───────────────────────────────────┼──────────┼─────────┼─────────────┤
│ Japan 10 Year Government Bond │ 0.200 │ 0.232 │ -0.002 │
├───────────────────────────────────┼──────────┼─────────┼─────────────┤
│ Australia 10 Year Government Bond │ 1.000 │ 3.703 │ -0.041 │
├───────────────────────────────────┼──────────┼─────────┼─────────────┤
│ China 10 Year Government Bond │ 2.760 │ 2.851 │ -0.010 │
└───────────────────────────────────┴──────────┴─────────┴─────────────┘
```
### Country Performance
Next to that, to better understand the current commodity market we can look into the <a href="/terminal/reference/economy/futures" target="_blank" rel="noreferrer noopener">futures</a> of a variety of commodities. For example, let's look at a general overview:
|Function Key |Description |
|:-----|-----:|
|gdp |Nominal Gross Domestic Product (GDP). |
|rgdp |Real Gross Domestic Product (GDP). |
|fgdp |Forecasts of nominal and real Gross Domestic Product (GDP). |
|debt |Government debt-to-GDP ratios. |
|cpi |Harmonized CPI. |
|ccpi |CPI Components. |
|balance |Government tax revenues. |
|spending |Government spending. |
|trust |Confidence in government surveys. |
```
(🦋) /economy/ $ futures
### Databases
Futures/Commodities [Source: Wall St. Journal]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━┓
┃ ┃ Price ┃ Chg ┃ %Chg ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━┩
│ Crude Oil Futures │ 113.10 │ 1.34 │ 1.20 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Brent Crude Futures │ 115.24 │ 1.44 │ 1.27 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Gold Futures │ 1823.50 │ 2.30 │ 0.13 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Silver Futures │ 20.690 │ -0.116 │ -0.56 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Natural Gas Futures │ 6.738 │ 0.187 │ 2.85 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Unleaded Gasoline Futures │ 3.8239 │ -0.0203 │ -0.53 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Copper Futures │ 3.7905 │ 0.0105 │ 0.28 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Corn Futures │ 653.75 │ -5.50 │ -0.83 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Wheat Futures │ 938.25 │ 2.25 │ 0.24 │
├───────────────────────────┼─────────┼─────────┼───────┤
│ Bloomberg Commodity Index │ 123.95 │ 1.25 │ 1.02 │
└───────────────────────────┴─────────┴─────────┴───────┘
```
|Function Key |Description |
|:-----|-----:|
|macro |Time series data by country and indicator. |
|treasury |Historical US Treasury rates. |
|fred |Query the FRED. |
|index |Historical daily time series for most major global indices. |
We can also show industry, sector and country performance with <a href="/terminal/reference/economy/performance" target="_blank" rel="noreferrer noopener">performance</a>. For example, looking at the `sectors` returns the following:
### Stored Datasets
```
(🦋) /economy/ $ performance -g sector
Group Performance Data
┏━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Name ┃ Week ┃ Month ┃ 3Month ┃ 6Month ┃ 1Year ┃ YTD ┃ Recom ┃ AvgVolume [1M] ┃ RelVolume ┃ Change ┃ Volume [1M] ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━┩
│ Utilities │ 0.04 │ -0.08 │ -0.07 │ -0.03 │ 0.06 │ -0.04 │ 2.37 │ 171.85 │ 0.50 │ -0.00 │ 8.05 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Technology │ 0.01 │ -0.10 │ -0.25 │ -0.31 │ -0.22 │ -0.31 │ 2.00 │ 1660.00 │ 1.08 │ -0.01 │ 168.13 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Real Estate │ 0.01 │ -0.06 │ -0.15 │ -0.21 │ -0.24 │ -0.22 │ 2.21 │ 396.36 │ 0.68 │ -0.02 │ 25.29 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Industrials │ 0.01 │ -0.09 │ -0.18 │ -0.20 │ -0.17 │ -0.20 │ 2.26 │ 656.49 │ 0.99 │ -0.01 │ 61.12 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Healthcare │ 0.03 │ -0.04 │ -0.10 │ -0.14 │ -0.12 │ -0.14 │ 2.07 │ 1530.00 │ 3.02 │ -0.00 │ 434.03 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Financial │ 0.01 │ -0.10 │ -0.19 │ -0.18 │ -0.16 │ -0.17 │ 2.26 │ 1010.00 │ 0.67 │ -0.00 │ 63.28 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Energy │ 0.04 │ -0.12 │ -0.03 │ 0.24 │ 0.29 │ 0.26 │ 2.21 │ 851.32 │ 0.82 │ 0.00 │ 65.35 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Consumer Defensive │ 0.02 │ -0.04 │ -0.08 │ -0.08 │ -0.05 │ -0.09 │ 2.28 │ 384.26 │ 0.84 │ -0.00 │ 30.44 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Consumer Cyclical │ 0.00 │ -0.07 │ -0.26 │ -0.31 │ -0.32 │ -0.31 │ 2.12 │ 1390.00 │ 1.25 │ -0.01 │ 163.60 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Communication Services │ 0.01 │ -0.05 │ -0.22 │ -0.28 │ -0.28 │ -0.28 │ 1.90 │ 745.84 │ 0.77 │ -0.01 │ 53.75 │
├────────────────────────┼───────┼───────┼────────┼────────┼───────┼───────┼───────┼────────────────┼───────────┼────────┼─────────────┤
│ Basic Materials │ -0.00 │ -0.15 │ -0.20 │ -0.13 │ -0.13 │ -0.13 │ 2.26 │ 529.64 │ 0.76 │ -0.01 │ 37.97 │
└────────────────────────┴───────┴───────┴────────┴────────┴───────┴───────┴───────┴────────────────┴───────────┴────────┴─────────────┘
```
### Economic Databases
Starting with the EconDB database (via <a href="/terminal/reference/economy/macro" target="_blank" rel="noreferrer noopener">macro</a>) a large selection of Economic data can be obtained. What can be obtained is easily found by typing `macro --show parameters` which returns the following:
```
(🦋) /economy/ $ macro --show parameters
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Parameter ┃ Name ┃ Period ┃ Description ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ RGDP │ Real gross domestic product │ Quarterly │ Inflation-adjusted measure that reflects the value of all goods and services produced by an economy in a given year (chain-linked │
│ │ │ │ series). │
├───────────┼─────────────────────────────────────────────────────┼───────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ RPRC │ Real private consumption │ Quarterly │ All purchases made by consumers adjusted by inflation (chain-linked series). │
├───────────┼─────────────────────────────────────────────────────┼───────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ RPUC │ Real public consumption │ Quarterly │ All purchases made by the government adjusted by inflation (chain-linked series). │
├───────────┼─────────────────────────────────────────────────────┼───────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ RGFCF │ Real gross fixed capital formation │ Quarterly │ The acquisition of produced assets adjusted by inflation (chain-linked series). │
├───────────┼─────────────────────────────────────────────────────┼───────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ REXP │ Real exports of goods and services │ Quarterly │ Transactions in goods and services from residents to non-residents adjusted for inflation (chain-linked series) │
├───────────┼─────────────────────────────────────────────────────┼───────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ RIMP │ Real imports of goods and services │ Quarterly │ Transactions in goods and services to residents from non-residents adjusted for inflation (chain-linked series) │
├───────────┼─────────────────────────────────────────────────────┼───────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
<continues>
```
As well as the available countries with `macro --show countries`:
```
(🦋) /economy/ $ macro --show countries
┏━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┓
┃ Country ┃ Currency ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩
│ Albania │ ALL │
├────────────────────────┼──────────┤
│ Argentina │ ARS │
├────────────────────────┼──────────┤
│ Australia │ AUD │
├────────────────────────┼──────────┤
│ Austria │ EUR │
├────────────────────────┼──────────┤
│ Azerbaijan │ AZN │
├────────────────────────┼──────────┤
│ Bangladesh │ BDT │
├────────────────────────┼──────────┤
│ Belarus │ BYR │
├────────────────────────┼──────────┤
│ Belgium │ EUR │
├────────────────────────┼──────────┤
<continues>
```
Then, with these parameters and countries, you can now plot macroeconomic data. For example, we can look at unemployment rate (`URATE`) of the Netherlands, Germany and France with the following:
```
(🦋) /economy/ $ macro --countries Netherlands Germany France --parameters URATE
```
This returns the following graph:
![Unemployment Rates](https://user-images.githubusercontent.com/46355364/176680030-b7936018-16ae-4dce-b652-5718977e9d57.png)
The FRED database similarly has a lot of macroeconomic data, do note that you need an API key to do this which is explained in more detail in the <a href="/terminal/usage/guides/changing-sources" target="_blank" rel="noreferrer noopener">Accessing other sources of data via API keys</a> section.
You have the ability to query the entire FRED database with the `-q` argument. For example, down below we look for datasets that are centered around inflation. The `-l` argument is set to show a maximum of 10 datasets:
```
(🦋) /economy/ $ fred -q inflation -l 10
Search results for inflation
┏━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Series ID ┃ Title ┃ Description ┃
┡━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ T10YIE │ 10-Year Breakeven Inflation Rate │ The breakeven inflation rate represents a measure of expected inflation derived from 10-Year │
│ │ │ Treasury Constant Maturity Securities (BC_10YEAR) and 10-Year Treasury Inflation-Indexed Constant │
│ │ │ Maturity Securities (TC_10YEAR). The latest value implies what market participants expect inflation │
│ │ │ to be in the next 10 years, on average. Starting with the update on June 21, 2019, the Treasury bond │
│ │ │ data used in calculating interest rate spreads is obtained directly from the U.S. Treasury │
│ │ │ Department (https://www.treasury.gov/resource-center/data-chart-center/interest- │
│ │ │ rates/Pages/TextView.aspx?data=yield). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ DFII10 │ Market Yield on U.S. Treasury Securities at │ For further information regarding treasury constant maturity data, please refer to the H.15 │
│ │ 10-Year Constant Maturity, Quoted on an Investment │ Statistical Release notes (https://www.federalreserve.gov/releases/h15/default.htm) and the Treasury │
│ │ Basis, Inflation-Indexed │ Yield Curve Methodology (https://home.treasury.gov/policy-issues/financing-the-government/interest- │
│ │ │ rate-statistics/treasury-yield-curve-methodology). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ T10YIEM │ 10-Year Breakeven Inflation Rate │ The breakeven inflation rate represents a measure of expected inflation derived from 10-Year │
│ │ │ Treasury Constant Maturity Securities (BC_10YEARM) and 10-Year Treasury Inflation-Indexed Constant │
│ │ │ Maturity Securities (TC_10YEARM). The latest value implies what market participants expect inflation │
│ │ │ to be in the next 10 years, on average. Starting with the update on June 21, 2019, the Treasury bond │
│ │ │ data used in calculating interest rate spreads is obtained directly from the U.S. Treasury │
│ │ │ Department (https://www.treasury.gov/resource-center/data-chart-center/interest- │
│ │ │ rates/Pages/TextView.aspx?data=yield). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ FII10 │ Market Yield on U.S. Treasury Securities at │ For further information regarding treasury constant maturity data, please refer to the H.15 │
│ │ 10-Year Constant Maturity, Quoted on an Investment │ Statistical Release notes (https://www.federalreserve.gov/releases/h15/default.htm) and the Treasury │
│ │ Basis, Inflation-Indexed │ Yield Curve Methodology (https://home.treasury.gov/policy-issues/financing-the-government/interest- │
│ │ │ rate-statistics/treasury-yield-curve-methodology). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ WFII10 │ Market Yield on U.S. Treasury Securities at │ For further information regarding treasury constant maturity data, please refer to the H.15 │
│ │ 10-Year Constant Maturity, Quoted on an Investment │ Statistical Release notes (https://www.federalreserve.gov/releases/h15/default.htm) and the Treasury │
│ │ Basis, Inflation-Indexed │ Yield Curve Methodology (https://home.treasury.gov/policy-issues/financing-the-government/interest- │
│ │ │ rate-statistics/treasury-yield-curve-methodology). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ RIFLGFCY10XIINA │ Market Yield on U.S. Treasury Securities at │ Averages of daily figures. For further information regarding treasury constant maturity data, │
│ │ 10-Year Constant Maturity, Quoted on an Investment │ please refer to the H.15 Statistical release notes │
│ │ Basis, Inflation-Indexed │ (https://www.federalreserve.gov/releases/h15/default.htm) and the Treasury Yield Curve Methodology │
│ │ │ (https://home.treasury.gov/policy-issues/financing-the-government/interest-rate-statistics/treasury- │
│ │ │ yield-curve-methodology). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ T5YIFR │ 5-Year, 5-Year Forward Inflation Expectation Rate │ This series is a measure of expected inflation (on average) over the five-year period that begins │
│ │ │ five years from today. This series is constructed as: (((((1+((BC_10YEAR- │
│ │ │ TC_10YEAR)/100))^10)/((1+((BC_5YEAR-TC_5YEAR)/100))^5))^0.2)-1)*100 where BC10_YEAR, TC_10YEAR, │
│ │ │ BC_5YEAR, and TC_5YEAR are the 10 year and 5 year nominal and inflation adjusted Treasury │
│ │ │ securities. All of those are the actual series IDs in FRED. Starting with the update on June 21, │
│ │ │ 2019, the Treasury bond data used in calculating interest rate spreads is obtained directly from the │
│ │ │ U.S. Treasury Department (https://www.treasury.gov/resource-center/data-chart-center/interest- │
│ │ │ rates/Pages/TextView.aspx?data=yield). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ T5YIE │ 5-Year Breakeven Inflation Rate │ The breakeven inflation rate represents a measure of expected inflation derived from 5-Year Treasury │
│ │ │ Constant Maturity Securities (BC_5YEAR) and 5-Year Treasury Inflation-Indexed Constant Maturity │
│ │ │ Securities (TC_5YEAR). The latest value implies what market participants expect inflation to be in │
│ │ │ the next 5 years, on average. Starting with the update on June 21, 2019, the Treasury bond data used │
│ │ │ in calculating interest rate spreads is obtained directly from the U.S. Treasury Department │
│ │ │ (https://www.treasury.gov/resource-center/data-chart-center/interest- │
│ │ │ rates/Pages/TextView.aspx?data=yield). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ T5YIFRM │ 5-Year, 5-Year Forward Inflation Expectation Rate │ This series is a measure of expected inflation (on average) over the five-year period that begins │
│ │ │ five years from today. This series is constructed as: (((((1+((BC_10YEAR- │
│ │ │ TC_10YEAR)/100))^10)/((1+((BC_5YEAR-TC_5YEAR)/100))^5))^0.2)-1)*100 where BC10_YEAR, TC_10YEAR, │
│ │ │ BC_5YEAR, and TC_5YEAR are the 10 year and 5 year nominal and inflation adjusted Treasury │
│ │ │ securities. All of those are the actual series IDs in FRED. Starting with the update on June 21, │
│ │ │ 2019, the Treasury bond data used in calculating interest rate spreads is obtained directly from the │
│ │ │ U.S. Treasury Department (https://www.treasury.gov/resource-center/data-chart-center/interest- │
│ │ │ rates/Pages/TextView.aspx?data=yield). │
├─────────────────┼────────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ T5YIEM │ 5-Year Breakeven Inflation Rate │ The breakeven inflation rate represents a measure of expected inflation derived from 5-Year Treasury │
│ │ │ Constant Maturity Securities (BC_5YEAR) and 5-Year Treasury Inflation-Indexed Constant Maturity │
│ │ │ Securities (TC_5YEAR). The latest value implies what market participants expect inflation to be in │
│ │ │ the next 5 years, on average. Starting with the update on June 21, 2019, the Treasury bond data used │
│ │ │ in calculating interest rate spreads is obtained directly from the U.S. Treasury Department │
│ │ │ (https://www.treasury.gov/resource-center/data-chart-center/interest- │
│ │ │ rates/Pages/TextView.aspx?data=yield). │
└─────────────────┴────────────────────────────────────────────────────┴──────────────────────────────────────────────────────────────────────────────────────────────────────┘
```
With this information, we can now plot datasets, e.g. the 5-year, 10-year, 20-year and 30-year break-even inflation rates, with the following. Note that I added some additional series not in the above table. This is because you can recognise the structure relatively easy of the break-even inflation rates, the number after the `T` refers to the amount of years.
```
(🦋) /economy/ $ fred T5YIEM,T10YIEM,T20YIEM,T30YIEM
```
Which returns the following graph:
![Break-Even Inflation Rates](https://user-images.githubusercontent.com/46355364/176680117-6d2b53e4-4980-42e6-a46c-4da34001ad46.png)
Furthermore, understanding the influence macroeconomic trends have to indices, the `index` command can be used. This has a large set of pre-configured indices but has the possibility to add your own if you enter the ticker. Which plots the following:
![Index Plot](https://user-images.githubusercontent.com/46355364/176680336-9ce60aa4-b2f7-4199-be42-62a8d78b1f5c.png)
This then all comes together within the <a href="/terminal/reference/economy/plot" target="_blank" rel="noreferrer noopener">plot</a> command where you can combine the datasets from the above commands into one graph. For example, it seems there is a relationship between the inflation rates and the unemployment rate (<a href="https://www.investopedia.com/articles/markets/081515/how-inflation-and-unemployment-are-related.asp" target="_blank" rel="noreferrer noopener">source</a>) which we can graphically show with:
```
(🦋) /economy/ $ macro -p URATE -s 2010-01-01
(🦋) /economy/ $ fred T5YIEM -s 2010-01-01
🦋) /economy/ $ plot --y1 United_States_URATE --y2 T5YIEM
```
Resulting in the following graph:
![Combine plots of Unemployment Rate and Break Even Inflation](https://user-images.githubusercontent.com/46355364/176680454-b878604e-08a2-474e-ad9f-3b695ee958d1.png)
|Function Key |Description |
|:-----|-----:|
|eval |A method for performing basic `eval` operations on a time series.
|plot |Plot multiple time series together. |
## Examples
Starting off, let's looking at current performance of energy futures with `futures`.
This section will demonstrate some basic operations within the menu.
```
(🦋) /economy/ $ futures energy
### events
Future Table [Source: FinViz]
┏━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━┓
┃ ┃ prevClose ┃ last ┃ change (%) ┃
┡━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━┩
│ Ethanol │ 2.16 │ 2.22 │ 2.78 │
├─────────────────┼───────────┼────────┼────────────┤
│ Gasoline RBOB │ 3.72 │ 3.66 │ -1.82 │
├─────────────────┼───────────┼────────┼────────────┤
│ Crude Oil Brent │ 116.26 │ 112.73 │ -3.04 │
├─────────────────┼───────────┼────────┼────────────┤
│ Natural Gas │ 6.50 │ 6.50 │ 0.03 │
├─────────────────┼───────────┼────────┼────────────┤
│ Heating Oil │ 3.96 │ 4.00 │ 1.06 │
├─────────────────┼───────────┼────────┼────────────┤
│ Crude Oil WTI │ 109.78 │ 110.02 │ 0.22 │
└─────────────────┴───────────┴────────┴────────────┘
A morning ritual might begin with checking the economic calendar for the day's - or week's - events. The `events` command can browse the calendar by country and date. By default, the current day for all countries will display in a table.
```console
/economy/events
```
This gives insights in the current future contracts and their (relative) performance. Here, we take a closer look at `Crude Oil Brent` by querying the FRED database, with `fred`, for a dataset that is relevant:
![Economic Calendar](https://user-images.githubusercontent.com/85772166/236106887-07732390-bee3-44e0-a69f-a71c8ee90a8e.png)
```
(🦋) /economy/ $ fred -q oil index
Search results for oil index
┏━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Series ID ┃ Title ┃ Description ┃
┡━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ OVXCLS │ CBOE Crude Oil ETF Volatility Index │ Exchange Traded Funds (ETFs) are shares of trusts that hold portfolios of stocks designed to closely │
│ │ │ track the price performance and yield of specific indices. Copyright, 2016, Chicago Board Options │
│ │ │ Exchange, Inc. Reprinted with permission. │
├─────────────────┼───────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ IPG211111CS │ Industrial Production: Mining, Quarrying, and Oil │ The industrial production (IP) index measures the real output of all relevant establishments located │
│ │ and Gas Extraction: Crude Oil (NAICS = 211111pt.) │ in the United States, regardless of their ownership, but not those located in U.S. territories. │
│ │ │ NAICS = 211111pt. Source Code: IP.G211111C.S │
├─────────────────┼───────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ PCU333132333132 │ Producer Price Index by Industry: Oil and Gas │ No description provided. │
│ │ Field Machinery and Equipment Manufacturing │ │
├─────────────────┼───────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ IPG211111CN │ Industrial Production: Mining, Quarrying, and Oil │ The industrial production (IP) index measures the real output of all relevant establishments located │
│ │ and Gas Extraction: Crude Oil (NAICS = 211111pt.) │ in the United States, regardless of their ownership, but not those located in U.S. territories. │
│ │ │ NAICS = 211111pt. Source Code: IP.G211111C.N │
├─────────────────┼───────────────────────────────────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ IPG211111CSQ │ Industrial Production: Mining, Quarrying, and Oil │ The industrial production (IP) index measures the real output of all relevant establishments located │
│ │ and Gas Extraction: Crude Oil (NAICS = 211111pt.) │ in the United States, regardless of their ownership, but not those located in U.S. territories. │
│ │ │ NAICS = 211111pt. Source Code: IP.G211111C.S │
└─────────────────┴───────────────────────────────────────────────────┴──────────────────────────────────────────────────────────────────────────────────────────────────────┘
To select a specific country, attach `--countries` to the command, then press the space bar. Use the up or down arrow keys to browse the choices.
![Economic Calendar Countries](https://user-images.githubusercontent.com/85772166/236106932-473c0f02-af80-49a6-bdb3-548ac1e689fa.png)
### overview
The `overview` fetches the headline levels and rates from the Wall Street Journal. Choose from of the categories by attaching the `-t` argument to the command.
```console
/economy/overview -t usbonds
```
Here, we take the `CBOE Crude OIL ETF Volatility Index` to get some understanding of how volatile oil is. Here, a period is defined from 2008 to 2015, showing the influence of the <a href="https://en.wikipedia.org/wiki/Financial_crisis_of_2007%E2%80%932008" target="_blank" rel="noreferrer noopener">Financial Crisis of 2008</a>.
![Overview](https://user-images.githubusercontent.com/85772166/236106975-961d7163-2ac8-4e05-b8df-34f2cf4908e7.png)
```
(🦋) /economy/ $ fred OVXCLS -s 2008-01-01 -e 2015-01-01
| | Rate (%) | Yld (%) | Yld Chg (%) |
|:-------------|-----------:|----------:|--------------:|
| 30-Year Bond | 3.625 | 3.686 | -0.028 |
| 10-Year Note | 3.5 | 3.343 | -0.085 |
| 7-Year Note | 3.5 | 3.323 | -0.122 |
| 5-Year Note | 3.5 | 3.305 | -0.162 |
| 3-Year Note | 3.75 | 3.513 | -0.18 |
| 2-Year Note | 3.875 | 3.838 | -0.144 |
| 1-Year Bill | 0 | 4.665 | -0.09 |
| 6-Month Bill | 0 | 4.98 | 0.005 |
| 3-Month Bill | 0 | 5.212 | 0.064 |
| 1-Month Bill | 0 | 4.452 | 0.114 |
### debt
Compare debt-to-GDP ratios between groups of countries by entering them as a comma-separated list.
```console
/economy/debt -c australia,norway,united_states,italy,japan
```
This plots the following graph:
![Debt-to-GDP](https://user-images.githubusercontent.com/85772166/236107021-231e7472-10a0-4208-a92e-fe56c81076c0.png)
![CBOE Crude OIL ETF Volatility Index](https://user-images.githubusercontent.com/46355364/176680559-2806bd91-2938-47be-8074-43b8f071aaad.png)
### index
A hypothesis could be that the more volatile the price of oil is, the lower the confidence of the consumers is. It is possible to visually depict this. First, let's plot the consumer confidence of Germany.
Major global indices are curated under the `index` command. Adding `--show` to the command will display a table with the list.
```
(🦋) /economy/ $ macro -p CONF -c Germany -s 2008-01-01 -e 2015-01-01
```console
index --show
```
![Consumer Confidence Germany](https://user-images.githubusercontent.com/46355364/176680603-1ace9534-f18a-4362-a1c0-d28c675d9415.png)
![Curated Index List](https://user-images.githubusercontent.com/85772166/236107143-a3e260e0-9530-4448-a552-12b46ae0aa72.png)
Now, combine these two graphs with the `plot` command. This helps in visually depicting a (negative) relationship.
The cumulative returns of an index is displayed instead of the levels by attaching `-r` to the command. Multiple indices can be queried simultaneously.
```
(🦋) /economy/ $ plot --y1 Germany_CONF --y2 OVXCLS
```console
index sp500,sp400,sp600 --start 2023-01-01 -r
```
![CBOE Crude OIL ETF Volatility Index and Consumer Confidence Germany](https://user-images.githubusercontent.com/46355364/176680645-79b8f44d-adc7-49e4-b749-80188f22850f.png)
![Indices](https://user-images.githubusercontent.com/85772166/236107229-410673db-e1ce-4e93-9e96-7821328e04dd.png)
### fred
To lookup FRED series by keywords attach, `-q`, to the `fred` command.
```console
fred -q PCE
```
![Fred Series](https://user-images.githubusercontent.com/85772166/236107269-8f126f17-3da7-4bb3-8acb-35f3ad783f84.png)
### plot
After requesting a time series, it gets populated under `Stored datasets`. Plot them together, on a shared or separate y-axis, by using the `plot` command.
![Multi-Axis Plots](https://user-images.githubusercontent.com/85772166/236107312-95ed4b92-e418-444c-b436-f45a1fc0a75d.png)
```console
plot --y1 PCE --y2 sp500
```
![Plot Multiple Time Series](https://user-images.githubusercontent.com/85772166/236107339-46037f4b-bc4f-458c-9f17-55a4cc6a61bc.png)