OpenBB/website/content/sdk/data-available/stocks/index.md

title, sidebar_position, description, keywords

title	sidebar_position	description	keywords
Stocks	0	This documentation page describes all the modules that are within the stocks menu of OpenBB.	stocks behavioural analysis comparison analysis discovery dark pool short data government trading insider trading fundamental analysis technical analysis

The Stocks module provides the functionality of the Stocks menu from the OpenBB Terminal. The list below are the SDK functions within the Stocks module and a short description:

Path	Type	Description
openbb.stocks.ba	Sub-Module	Behavioural Analysis
openbb.stocks.ca	Sub-Module	Comparison Analysis
openbb.stocks.candle	Function	OHLC + Volume + Moving Averages Chart
openbb.stocks.disc	Sub-Module	Stock Discovery
openbb.stocks.dps	Sub-Module	Dark Pools & Shorts
openbb.stocks.fa	Sub-Module	Fundamental Analysis & Future Estimations
openbb.stocks.gov	Sub-Module	US Government, Lobbying & Representative Activity
openbb.stocks.ins	Sub-Module	Corporate Insider Activity (SEC Form 4)
openbb.stocks.load	Function	Load Historical OHLC+V Data
openbb.stocks.options	Sub-Module	Options
openbb.stocks.qa	Sub-Module	Stocks-Only Quantitative Analysis
openbb.stocks.quote	Function	Last Price and Performance Data (FinancialModelingPrep)
openbb.stocks.screener	Sub-Module	Stock Screener
openbb.stocks.search	Function	Find Stocks
openbb.stocks.sia	Sub-Module	Sector & Industry Analysis
openbb.stocks.ta	Sub-Module	Stocks-Only Technical Analysis
openbb.stocks.th	Sub-Module	Trading Hours (Market Status)
openbb.stocks.tob	Function	Top of Book (CBOE)

How to use

help(openbb.stocks)

Most items in openbb.stocks are sub-modules. The objective of this guide is to introduce the functions at the top-level and to demonstrate a selection of functions from the sub-modules.

Examples

The code snippets in the following section will assume that the import block contains:

import pandas as pd
from datetime import datetime
from openbb_terminal.sdk import openbb

Load

The first step in a workflow might be to collect historical price data. The load function has the ability to request data from multiple sources. The choices for source are currently:

• YahooFinance (default)
• AlphaVantage
• Polygon
• EODHD

spy_monthly = openbb.stocks.load(
    symbol = 'SPY',
    start_date = '1990-01-01',
    interval = 1440,
    prepost = False,
    source = 'YahooFinance',
    weekly = False,
    monthly = True,
)
spy_monthly.head(3)

date	Open	High	Low	Close	Adj Close	Volume
1993-02-01 00:00:00	43.9688	45.125	42.8125	44.4062	25.6043	5.4176e+06
1993-03-01 00:00:00	44.5625	45.8438	44.2188	45.1875	26.0548	3.0192e+06
1993-04-01 00:00:00	45.25	45.25	43.2812	44.0312	25.508	2.6972e+06

There are source-dependent differences to the DataFrame returned. For example, compare the above with below:

spy_monthly = openbb.stocks.load(
    symbol = 'SPY',
    start_date = '1990-01-01',
    interval = 1440,
    prepost = False,
    source = 'Polygon',
    weekly = False,
    monthly = True,
)
spy_monthly.head(3)

date	Volume	vw	Open	Adj Close	High	Low	Transactions	Close
2022-09-01 04:00:00	1.99492e+09	382.507	392.89	357.18	411.73	357.04	1.35653e+07	357.18
2022-10-01 04:00:00	2.02389e+09	370.918	361.08	386.21	389.52	348.11	1.38047e+07	386.21
2022-11-01 04:00:00	1.17559e+09	386.119	390.14	394.28	402.31	368.79	8.34067e+06	394.28

Candle

OHLC DataFrames can be passed through the Candle function to display a chart.

openbb.stocks.candle(data = spy_monthly, symbol = 'SPY - Monthly Candles')

The candle function is also aware if a ticker is being passed. This makes it unnecessary to create a DataFrame if the objective is only to display the chart.

openbb.stocks.candle('SPY')

Add moving averages to the chart with:

openbb.stocks.candle('SPY', ma = [50,150])

Search

Search for companies by name with the search function, with optional filters for sector, industry, and region:

openbb.stocks.search(sector = 'Energy', country = 'United Kingdom', query = 'oil')

		long_name	country	sector	industry	exchange
0	3NO.F	Nostrum Oil & Gas PLC	United Kingdom	Energy	Oil & Gas E&P	nan
1	BOIL.L	Baron Oil Plc	United Kingdom	Energy	Oil & Gas E&P	nan
2	EGN.F	Europa Oil & Gas (Holdings) plc	United Kingdom	Energy	Oil & Gas E&P	nan
3	EOG.L	Europa Oil & Gas (Holdings) plc	United Kingdom	Energy	Oil & Gas E&P	nan
4	GHA.F	Baron Oil Plc	United Kingdom	Energy	Oil & Gas E&P	nan

...continued

Quote

Watchlists are easy to make. Get the last price and performance data for multiple tickers by looping the quote function:

spdr_sectors = ['SPY', 'XLE', 'XLB', 'XLI', 'XLP', 'XLY', 'XLV', 'XLF', 'XLK', 'XLC', 'XLU', 'XLRE']

quotes: object = []
symbols = spdr_sectors
for symbols in spdr_sectors:
    quote = openbb.stocks.quote(symbols).transpose()
    quotes.append(quote)

quotes = pd.concat(quotes)

quotes

	Symbol	Name	Price	Changes percentage	Change	Day low	Day high	Year high	Year low	Market cap	Price avg50	Price avg200	Exchange	Volume	Avg volume	Open	Previous close	Eps	Pe	Earnings announcement	Shares outstanding	Timestamp
0	SPY	SPDR S&P 500 ETF Trust	393.74	0.9616	3.75	390.08	394.17	462.07	348.11	361.367 B	399.841	392.797	AMEX	88.857 M	89590689	390.8	389.99	19.9365	19.75		917.782 M	1679342401
0	XLE	Energy Select Sector SPDR Fund	77.7	2.0024	1.5253	76.1	78.2	94.71	65.48	14.485 B	86.6584	82.6697	AMEX	25.791 M	19906166	76.1	76.1747	10.86	7.15		186.424 M	1679342400
0	XLB	Materials Select Sector SPDR Fund	76.73	2.0581	1.5473	75.77	76.77	91.49	66.85	5.519 B	81.7186	77.8203	AMEX	7.327 M	5830645	75.77	75.1827	5.16256	14.86		71.924 M	1679342400
0	XLI	Industrial Select Sector SPDR Fund	97.55	1.3242	1.2749	96.71	97.79	105.23	82.75	13.328 B	101.103	95.1877	AMEX	14.078 M	11957477	96.71	96.2751	4.6974	20.77		136.626 M	1679342400
0	XLP	Consumer Staples Select Sector SPDR Fund	72.76	1.386	0.9947	72.01	72.83	81.34	66.18	15.292 B	73.092	72.9574	AMEX	14.127 M	10950449	72.04	71.7653	2.88675	25.2		210.172 M	1679342400
0	XLY	Consumer Discretionary Select Sector SPDR Fund	141.52	0.433	0.6102	139.75	142.39	192.19	126	17.018 B	143.901	146.454	AMEX	5.863 M	5416313	140.74	140.91	6.27203	22.56		120.253 M	1679342400
0	XLV	Health Care Select Sector SPDR Fund	126.96	1.2675	1.5891	125.58	127.145	143.42	118.75	25.064 B	131.092	130.376	AMEX	10.584 M	8826462	125.58	125.371	5.92017	21.45		197.415 M	1679342400
0	XLF	Financial Select Sector SPDR Fund	31.17	1.1114	0.3426	31.025	31.44	40.01	29.59	27.537 B	35.4068	33.8593	AMEX	74.917 M	50017188	31.07	30.8274	2.57075	12.12		883.445 M	1679342400
0	XLK	Technology Select Sector SPDR Fund	143.53	0.2693	0.3855	141.82	143.7	163.65	112.97	39.048 B	136.542	132.924	AMEX	5.924 M	7283266	142.89	143.145	5.1111	28.08		272.056 M	1679342400
0	XLC	Communication Services Select Sector SPDR Fund	55.27	0.7474	0.41	54.71	55.41	71.57	44.86	0	54.1118	52.9782	AMEX	7.189 M	6117298	54.91	54.86	2.87114	19.25		0	1679342400
0	XLU	Utilities Select Sector SPDR Fund	67	0.7818	0.5197	66.56	67.22	78.22	60.35	10.939 B	68.0158	69.9207	AMEX	19.265 M	12304022	66.58	66.4803	2.88295	23.24		163.274 M	1679342400
0	XLRE	The Real Estate Select Sector SPDR Fund	36.36	1.0727	0.3859	35.87	36.4932	50.97	33.125	0	38.953	39.4885	AMEX	4.963 M	6039455	36.06	35.9741	1.30938	27.77		0	1679342400

TOB

Top of Book gets the size and price at the top of the order book.

bid,ask = openbb.stocks.tob('SPY')
quote_tob = bid.join(ask, lsuffix= ': Bid', rsuffix = ': Ask')

quote_tob

	Size: Bid	Price: Bid	Size: Ask	Price: Ask
0	100	394.85	100	395
1	100	394.8	300	395.05
2	100	394.7	100	395.07
3	100	394.68	200	395.25
4	100	394.65	100	395.29

Filings

Get the most-recent form submissions to the SEC.

filings = openbb.stocks.disc.filings()
filings.head(3)

Date	Ticker	CIK	Form Type	Title	URL
2023-03-20 17:30:26	TLGA	1827871	10-K	10-K - TLG Acquisition One Corp. (0001827871) (Filer)	https://www.sec.gov/Archives/edgar/data/1827871/000119312523074903/0001193125-23-074903-index.htm
2023-03-20 17:30:26	TLGA	1827871	10-K	10-K - TLG Acquisition One Corp. (0001827871) (Filer)	https://www.sec.gov/Archives/edgar/data/1827871/000119312523074903/0001193125-23-074903-index.htm
2023-03-20 17:30:26	TLGA-UN	1827871	10-K	10-K - TLG Acquisition One Corp. (0001827871) (Filer)	https://www.sec.gov/Archives/edgar/data/1827871/000119312523074903/0001193125-23-074903-index.htm
2023-03-20 17:30:26	TLGA-UN	1827871	10-K	10-K - TLG Acquisition One Corp. (0001827871) (Filer)	https://www.sec.gov/Archives/edgar/data/1827871/000119312523074903/0001193125-23-074903-index.htm
2023-03-20 17:30:26	TLGA-WT	1827871	10-K	10-K - TLG Acquisition One Corp. (0001827871) (Filer)	https://www.sec.gov/Archives/edgar/data/1827871/000119312523074903/0001193125-23-074903-index.htm

Filter them to be from the current day only:

today = filings.filter(like = datetime.now().strftime("%Y-%m-%d"), axis = 0)

Screener

Grab the list of filtered tickers and put them through the comparison analysis screener and get an overview:

tickers = today['Ticker'].to_list()
screener_results = openbb.stocks.ca.screener(similar = tickers, data_type = 'overview')
screener_results = screener_results.sort_values(by = ['Market Cap'], ascending = False).convert_dtypes()

screener_results.head(5)

	Ticker	Company	Sector	Industry	Country	Market Cap	P/E	Price	Change	Volume
72	NVO	Novo Nordisk A/S	Healthcare	Biotechnology	Denmark	2.4814e+11	41.42	143.59	0.0298	1242167
34	EQNR	Equinor ASA	Energy	Oil & Gas Integrated	Norway	8.591e+10	3.02	27.34	0.0096	4154740
46	GSK	GSK plc	Healthcare	Drug Manufacturers - General	United Kingdom	7.026e+10	12.29	34.93	0.0252	2973805
105	UBS	UBS Group AG	Financial	Banks - Diversified	Switzerland	6.783e+10	8.39	18.8	0.033	40598414
83	RELX	RELX PLC	Communication Services	Publishing	United Kingdom	5.97e+10	30.52	31.31	0.0205	620949

This type of framework can be used to create any type of custom screener. For example, the most popular tickers on Stocktwits:

stocktwits = openbb.stocks.ba.trending()
stocktwits = pd.DataFrame(stocktwits).sort_values(by = 'Watchlist Count', ascending = False)
tickers = stocktwits['Ticker'].to_list()
stocktwits.head(10)

	Ticker	Watchlist Count	Name
18	NVDA	409301	NVIDIA Corp
12	AMC	406952	AMC Entertainment Holdings Inc
5	WMT	109864	Walmart Inc
6	MRNA	100705	Moderna Inc
21	PFE	87229	Pfizer Inc.
4	DWAC	66122	Digital World Acquisition Corp
29	CSCO	54458	Cisco Systems, Inc.
0	SAVA	49063	Cassava Sciences Inc
8	TDOC	38657	Teladoc Health Inc
16	PENN	38277	Penn National Gaming, Inc.

Filter the results by market cap:

screener_results = openbb.stocks.ca.screener(similar = tickers, data_type = 'overview')
screener_results = screener_results.sort_values(by = ['Market Cap'], ascending = False)

screener_results.head(5)

	Ticker	Company	Sector	Industry	Country	Market Cap	P/E	Price	Change	Volume
15	NVDA	NVIDIA Corporation	Technology	Semiconductors	USA	3.9217e+11	53.53	163.66	0.0024	3.16641e+07
26	WMT	Walmart Inc.	Consumer Defensive	Discount Stores	USA	3.864e+11	28.46	140.5	-0.0146	5.33372e+06
18	PFE	Pfizer Inc.	Healthcare	Drug Manufacturers - General	USA	2.6591e+11	9.03	49.36	0.037	1.07892e+07
4	BLK	BlackRock, Inc.	Financial	Asset Management	USA	1.1412e+11	21.34	747.95	-0.0346	742602
25	TGT	Target Corporation	Consumer Defensive	Discount Stores	USA	7.566e+10	19.68	175.67	0.0136	2.45293e+06

...continued

SEC

Get the links for SEC filings belonging to a company:

openbb.stocks.fa.sec(symbol = 'WMT')

Filing Date	Document Date	Type	Category	Amended	Link
09/09/2022	09/06/2022	8-K	Special Events		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=16074059
09/02/2022	07/31/2022	10-Q	Quarterly Reports		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=16064659
08/17/2022	08/17/2022	8-K	Special Events		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=16026629
08/17/2022	08/17/2022	8-K	Special Events		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=16025172
08/16/2022	08/16/2022	8-K	Special Events		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=16021891
07/25/2022	07/25/2022	8-K	Special Events		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=15964414
07/21/2022	N/A	SC 13D/A	N/A	*	https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=15959675
06/28/2022	06/28/2022	8-K	Special Events		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=15918852
06/21/2022	N/A	SC 13D	N/A		https://www.marketwatch.com/investing/stock/wmt/financials/secfilings?docid=15900809

...continued

Insiders Trading

View insider activity on the stock:

openbb.stocks.ins.lins(symbol = 'WMT')

Date	Relationship	Transaction	#Shares	Cost	Value ($)	#Shares Total	Insider Trading	SEC Form 4
Oct 27	President and CEO	Sale	9,708	141.18	1,370,617	1,478,337	McMillon C Douglas	Oct 28 06:14 PM
Oct 27	Executive Vice President	Sale	4,375	140.94	616,612	263,809	Furner John R.	Oct 28 06:11 PM
Sep 22	Executive Vice President	Sale	4,375	134.38	587,912	268,183	Furner John R.	Sep 23 05:21 PM
Sep 22	President and CEO	Sale	9,708	134.04	1,301,309	1,488,043	McMillon C Douglas	Sep 23 05:18 PM
Aug 25	Director	Sale	347,542	135.66	47,145,880	282,330,635	WALTON S ROBSON	Aug 26 06:36 PM

...continued

Income Statement Comparison

Income statements from multiple companies can be easily referenced:

openbb.stocks.ca.income(similar = ['WMT', 'TGT', 'AMZN'], quarter = True)

Item	31-Jul-2022: WMT	31-Jul-2022: TGT	30-Sep-2022: AMZN
Sales/Revenue	152.86B	26.04B	127.1B
Sales Growth	7.97%	3.44%	4.84%
Cost of Goods Sold (COGS) incl. D&A	115.84B	20.71B	70.27B
COGS Growth	8.41%	8.67%	5.79%
COGS excluding D&A	113.14B	20.06B	60.06B
Depreciation & Amortization Expense	2.7B	650M	10.2B
Depreciation	2.7B	-	-
Amortization of Intangibles	-	-	-
Gross Income	37.02B	5.32B	56.83B
Gross Income Growth	6.62%	-12.85%	3.69%
Gross Profit Margin	24.22%	20.44%	44.71%
SG&A Expense	30.17B	4.98B	54.14B
SGA Growth	3.30%	4.98%	5.33%
Research & Development	-	-	19.49B
Other SG&A	-	-	-
Other Operating Expense	-	-	-
Unusual Expense	(238M)	27M	(2.04B)
EBIT after Unusual Expense	238M	(27M)	2.04B
Non Operating Income/Expense	-	8M	(1.45B)
Non-Operating Interest Income	31M	-	277M

...continued

Ratios

Get historical fundamental ratios for a company:

openbb.stocks.fa.ratios(symbol = 'WMT')

	2022	2021	2020	2019	2018
Period	FY	FY	FY	FY	FY
Current ratio	0.928	0.972	0.795	0.799	0.760
Quick ratio	0.264	0.262	0.202	0.181	0.158
Cash ratio	0.169	0.191	0.122	0.100	0.086
Days of sales outstanding	5.277	4.253	4.378	4.458	4.095
Days of inventory outstanding	48.080	39.034	41.101	41.937	42.799
Operating cycle	53.357	43.287	45.479	46.395	46.894
Days of payables outstanding	47.017	42.674	43.449	44.580	45.056
Cash conversion cycle	6.340	0.613	2.030	1.814	1.838
Gross profit margin	0.251	0.248	0.247	0.251	0.254
Operating profit margin	0.045	0.040	0.039	0.043	0.041
Pretax profit margin	0.033	0.037	0.038	0.022	0.030
Net profit margin	0.024	0.024	0.028	0.013	0.020

...continued

Take just the ratio needed by filtering the index:

ratios = openbb.stocks.fa.ratios(symbol = 'WMT', limit = 20)
ratios.filter(like = 'Price earnings to growth ratio', axis = 0)

	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010	2009	2008	2007	2006	2005	2004	2003
Price earnings to growth ratio	10.202	-3.163	0.16	-1.401	-1.069	-4.092	-1.501	4.777	-5.487	1.293	9.68	0.559	1.585	1.637	1.022	15.761	1.498	1.358	1.953	1.233

Be sure to check out the introduction guides for each sub-module as well.