{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "83014ba8", "metadata": {}, "source": [ "

\n", " \"Logo\"\n", "\n", "\n", "[![GitHub Sponsors](https://img.shields.io/badge/Sponsor_this_Project-grey?logo=github)](https://github.com/sponsors/JerBouma)\n", "[![Documentation](https://img.shields.io/badge/Documentation-grey?logo=readme)](https://www.jeroenbouma.com/projects/financedatabase)\n", "[![Supported Python Versions](https://img.shields.io/pypi/pyversions/financedatabase)](https://pypi.org/project/financedatabase/)\n", "[![PYPI Version](https://img.shields.io/pypi/v/financedatabase)](https://pypi.org/project/financedatabase/)\n", "[![PYPI Downloads](https://static.pepy.tech/badge/financedatabase/month)](https://pepy.tech/project/financedatabase)\n", "\n", "The **FinanceDatabase** serves the role of providing anyone with any type of financial product categorisation entirely for free. To be able to achieve this, the FinanceDatabase relies on involvement from the community to add, edit and remove tickers over time. This is made easy enough that anyone, even with a lack of coding experience can contribute because of the usage of CSV files that can be manually edited. I'd like to invite you to go to the **[Contributing Guidelines](https://github.com/JerBouma/FinanceDatabase/blob/main/CONTRIBUTING.md)** to understand how you can help. Thank you!\n", "\n", "As a private investor, the sheer amount of information that can be found on the internet is rather daunting. Trying to \n", "understand what type of companies or ETFs are available is incredibly challenging with there being millions of\n", "companies and derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found\n", "simply because they are known to the public (for example, Microsoft, Tesla, S&P500 ETF or an All-World ETF). However, \n", "what else is out there is often unknown.\n", "\n", "**This database tries to solve that**. It features 300.000+ symbols containing Equities, ETFs, Funds, Indices, \n", "Currencies, Cryptocurrencies and Money Markets. It therefore allows you to obtain a broad overview of sectors,\n", "industries, types of investments and much more.\n", "\n", "The aim of this database is explicitly _not_ to provide up-to-date fundamentals or stock data as those can be obtained \n", "with ease (with the help of this database) by using the [FinanceToolkit](https://github.com/JerBouma/FinanceToolkit). Instead, it gives insights into the products \n", "that exist in each country, industry and sector and gives the most essential information about each product. With \n", "this information, you can analyse specific areas of the financial world and/or find a product that is hard to find.\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "3a2a1a46", "metadata": {}, "source": [ "# Installation\n", "To install the FinanceDatabase it simply requires the following:\n", "\n", "```\n", "pip install financedatabase -U\n", "```\n", "\n", "From within Python use:\n", "\n", "```python\n", "import financedatabase as fd\n", "```" ] }, { "cell_type": "code", "execution_count": null, "id": "e847b00b", "metadata": {}, "outputs": [], "source": [ "import financedatabase as fd\n", "\n", "# Optional Financial Modeling Prep API key for Finance Toolkit functionality\n", "API_KEY = \"FINANCIAL_MODELING_PREP_API_KEY\"" ] }, { "attachments": {}, "cell_type": "markdown", "id": "d45b268e", "metadata": {}, "source": [ "Initalization of each asset class is only required once. It is therefore important you save the class to a variable so that you can query the database much quicker. A simple example is shown below." ] }, { "cell_type": "code", "execution_count": 2, "id": "6e0271f5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "

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namesummarycurrencysectorindustry_groupindustryexchangemarketcountrystatecityzipcodewebsitemarket_capisincusipfigicomposite_figishareclass_figi
symbol
000002.SZChina Vanke Co., Ltd.China Vanke Co., Ltd., together with its subsi...CNYReal EstateReal EstateReal Estate Management & DevelopmentSHZShenzhen Stock ExchangeChinaNaNShenzhen518083http://www.vanke.comLarge CapCNE100001SR9NaNNaNNaNNaN
000004.SZtwotwo is a blank check company. The company was ...CNYFinancialsDiversified FinancialsDiversified Financial ServicesSHZShenzhen Stock ExchangeUnited StatesCASan Francisco94129http://www.sz000004.cnMicro CapNaNNaNNaNNaNNaN
000005.SZShenzhen Fountain CorporationShenzhen Fountain Corporation engages in real ...CNYReal EstateReal EstateReal Estate Management & DevelopmentSHZShenzhen Stock ExchangeChinaNaNShenzhen518001http://www.fountain.com.cnSmall CapCNE0000001L7NaNNaNNaNNaN
000006.SZShenzhen Zhenye (Group) Co.,Ltd.Shenzhen Zhenye (Group) Co.,Ltd. engages in th...CNYReal EstateReal EstateReal Estate Management & DevelopmentSHZShenzhen Stock ExchangeChinaNaNShenzhen518008http://www.zhenye.comSmall CapCNE000000164NaNNaNNaNNaN
000007.SZShenzhen Quanxinhao Co., Ltd.Shenzhen Quanxinhao Co., Ltd. owns and operate...CNYConsumer DiscretionaryConsumer ServicesHotels, Restaurants & LeisureSHZShenzhen Stock ExchangeChinaNaNShenzhen518031http://www.sz000007.comMicro CapCNE0000000P0NaNNaNNaNNaN
............................................................
ZZMS.SGCommerzbank AGCommerzbank AG provides banking and capital ma...EURFinancialsBanksBanksSTUStuttgart Stock ExchangeGermanyNaNFrankfurt am Main60311http://www.commerzbank.comMid CapNaNNaNNaNNaNNaN
ZZVA.BEDeutsche Bank AGNaNEURNaNNaNNaNBERBerlin Stock ExchangeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
ZZVA.DUDeutsche Bank AGNaNEURNaNNaNNaNDUSDusseldorf Stock ExchangeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
ZZZ.TOSleep Country Canada Holdings Inc.Sleep Country Canada Holdings Inc., together w...CADConsumer DiscretionaryRetailingSpecialty RetailTORTSX Toronto ExchangeCanadaONBramptonL6T 4N8http://www.sleepcountry.caSmall CapNaNNaNNaNNaNNaN
ZZZOFoneone does not have significant operations. It i...USDFinancialsDiversified FinancialsDiversified Financial ServicesPNKOTC Bulletin BoardUnited StatesCASan Francisco94129http://www.a-star.coSmall CapNaNNaNNaNNaNNaN
\n", "

159182 rows × 19 columns

\n", "
" ], "text/plain": [ " name \\\n", "symbol \n", "000002.SZ China Vanke Co., Ltd. \n", "000004.SZ two \n", "000005.SZ Shenzhen Fountain Corporation \n", "000006.SZ Shenzhen Zhenye (Group) Co.,Ltd. \n", "000007.SZ Shenzhen Quanxinhao Co., Ltd. \n", "... ... \n", "ZZMS.SG Commerzbank AG \n", "ZZVA.BE Deutsche Bank AG \n", "ZZVA.DU Deutsche Bank AG \n", "ZZZ.TO Sleep Country Canada Holdings Inc. \n", "ZZZOF one \n", "\n", " summary currency \\\n", "symbol \n", "000002.SZ China Vanke Co., Ltd., together with its subsi... CNY \n", "000004.SZ two is a blank check company. The company was ... CNY \n", "000005.SZ Shenzhen Fountain Corporation engages in real ... CNY \n", "000006.SZ Shenzhen Zhenye (Group) Co.,Ltd. engages in th... CNY \n", "000007.SZ Shenzhen Quanxinhao Co., Ltd. owns and operate... CNY \n", "... ... ... \n", "ZZMS.SG Commerzbank AG provides banking and capital ma... EUR \n", "ZZVA.BE NaN EUR \n", "ZZVA.DU NaN EUR \n", "ZZZ.TO Sleep Country Canada Holdings Inc., together w... CAD \n", "ZZZOF one does not have significant operations. It i... USD \n", "\n", " sector industry_group \\\n", "symbol \n", "000002.SZ Real Estate Real Estate \n", "000004.SZ Financials Diversified Financials \n", "000005.SZ Real Estate Real Estate \n", "000006.SZ Real Estate Real Estate \n", "000007.SZ Consumer Discretionary Consumer Services \n", "... ... ... \n", "ZZMS.SG Financials Banks \n", "ZZVA.BE NaN NaN \n", "ZZVA.DU NaN NaN \n", "ZZZ.TO Consumer Discretionary Retailing \n", "ZZZOF Financials Diversified Financials \n", "\n", " industry exchange \\\n", "symbol \n", "000002.SZ Real Estate Management & Development SHZ \n", "000004.SZ Diversified Financial Services SHZ \n", "000005.SZ Real Estate Management & Development SHZ \n", "000006.SZ Real Estate Management & Development SHZ \n", "000007.SZ Hotels, Restaurants & Leisure SHZ \n", "... ... ... \n", "ZZMS.SG Banks STU \n", "ZZVA.BE NaN BER \n", "ZZVA.DU NaN DUS \n", "ZZZ.TO Specialty Retail TOR \n", "ZZZOF Diversified Financial Services PNK \n", "\n", " market country state city \\\n", "symbol \n", "000002.SZ Shenzhen Stock Exchange China NaN Shenzhen \n", "000004.SZ Shenzhen Stock Exchange United States CA San Francisco \n", "000005.SZ Shenzhen Stock Exchange China NaN Shenzhen \n", "000006.SZ Shenzhen Stock Exchange China NaN Shenzhen \n", "000007.SZ Shenzhen Stock Exchange China NaN Shenzhen \n", "... ... ... ... ... \n", "ZZMS.SG Stuttgart Stock Exchange Germany NaN Frankfurt am Main \n", "ZZVA.BE Berlin Stock Exchange NaN NaN NaN \n", "ZZVA.DU Dusseldorf Stock Exchange NaN NaN NaN \n", "ZZZ.TO TSX Toronto Exchange Canada ON Brampton \n", "ZZZOF OTC Bulletin Board United States CA San Francisco \n", "\n", " zipcode website market_cap isin cusip \\\n", "symbol \n", "000002.SZ 518083 http://www.vanke.com Large Cap CNE100001SR9 NaN \n", "000004.SZ 94129 http://www.sz000004.cn Micro Cap NaN NaN \n", "000005.SZ 518001 http://www.fountain.com.cn Small Cap CNE0000001L7 NaN \n", "000006.SZ 518008 http://www.zhenye.com Small Cap CNE000000164 NaN \n", "000007.SZ 518031 http://www.sz000007.com Micro Cap CNE0000000P0 NaN \n", "... ... ... ... ... ... \n", "ZZMS.SG 60311 http://www.commerzbank.com Mid Cap NaN NaN \n", "ZZVA.BE NaN NaN NaN NaN NaN \n", "ZZVA.DU NaN NaN NaN NaN NaN \n", "ZZZ.TO L6T 4N8 http://www.sleepcountry.ca Small Cap NaN NaN \n", "ZZZOF 94129 http://www.a-star.co Small Cap NaN NaN \n", "\n", " figi composite_figi shareclass_figi \n", "symbol \n", "000002.SZ NaN NaN NaN \n", "000004.SZ NaN NaN NaN \n", "000005.SZ NaN NaN NaN \n", "000006.SZ NaN NaN NaN \n", "000007.SZ NaN NaN NaN \n", "... ... ... ... \n", "ZZMS.SG NaN NaN NaN \n", "ZZVA.BE NaN NaN NaN \n", "ZZVA.DU NaN NaN NaN \n", "ZZZ.TO NaN NaN NaN \n", "ZZZOF NaN NaN NaN \n", "\n", "[159182 rows x 19 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Initialize the Equities database\n", "equities = fd.Equities()\n", "\n", "# Obtain all countries from the database\n", "equities.select()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "c578765b", "metadata": {}, "source": [ "With `show_options` all possible options are given per column. **This is useful as it doesn't require loading the larger data files.** For example, obtaining all options for equities is done as follow:" ] }, { "cell_type": "code", "execution_count": 3, "id": "a8f1241b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'currency': array(['ARS', 'AUD', 'BRL', 'CAD', 'CHF', 'CLP', 'CNY', 'COP', 'CZK',\n", " 'DKK', 'EUR', 'GBP', 'HKD', 'HUF', 'IDR', 'ILA', 'ILS', 'INR',\n", " 'ISK', 'JPY', 'KES', 'KRW', 'LKR', 'MXN', 'MYR', 'NOK', 'NZD',\n", " 'PEN', 'PHP', 'PLN', 'QAR', 'RUB', 'SAR', 'SEK', 'SGD', 'THB',\n", " 'TRY', 'TWD', 'USD', 'ZAC', 'ZAR'], dtype=object),\n", " 'sector': array(['Communication Services', 'Consumer Discretionary',\n", " 'Consumer Staples', 'Energy', 'Financials', 'Health Care',\n", " 'Industrials', 'Information Technology', 'Materials',\n", " 'Real Estate', 'Utilities'], dtype=object),\n", " 'industry_group': array(['Automobiles & Components', 'Banks', 'Capital Goods',\n", " 'Commercial & Professional Services',\n", " 'Consumer Durables & Apparel', 'Consumer Services',\n", " 'Diversified Financials', 'Energy', 'Food & Staples Retailing',\n", " 'Food, Beverage & Tobacco', 'Health Care Equipment & Services',\n", " 'Household & Personal Products', 'Insurance', 'Materials',\n", " 'Media & Entertainment',\n", " 'Pharmaceuticals, Biotechnology & Life Sciences', 'Real Estate',\n", " 'Retailing', 'Semiconductors & Semiconductor Equipment',\n", " 'Software & Services', 'Technology Hardware & Equipment',\n", " 'Telecommunication Services', 'Transportation', 'Utilities'],\n", " dtype=object),\n", " 'industry': array(['Aerospace & Defense', 'Air Freight & Logistics', 'Airlines',\n", " 'Auto Components', 'Automobiles', 'Banks', 'Beverages',\n", " 'Biotechnology', 'Building Products', 'Capital Markets',\n", " 'Chemicals', 'Commercial Services & Supplies',\n", " 'Communications Equipment', 'Construction & Engineering',\n", " 'Construction Materials', 'Consumer Finance', 'Distributors',\n", " 'Diversified Consumer Services', 'Diversified Financial Services',\n", " 'Diversified Telecommunication Services', 'Electric Utilities',\n", " 'Electrical Equipment',\n", " 'Electronic Equipment, Instruments & Components',\n", " 'Energy Equipment & Services', 'Entertainment',\n", " 'Equity Real Estate Investment Trusts (REITs)',\n", " 'Food & Staples Retailing', 'Food Products', 'Gas Utilities',\n", " 'Health Care Equipment & Supplies',\n", " 'Health Care Providers & Services', 'Health Care Technology',\n", " 'Hotels, Restaurants & Leisure', 'Household Durables',\n", " 'Household Products', 'IT Services',\n", " 'Independent Power and Renewable Electricity Producers',\n", " 'Industrial Conglomerates', 'Insurance',\n", " 'Interactive Media & Services',\n", " 'Internet & Direct Marketing Retail', 'Machinery', 'Marine',\n", " 'Media', 'Metals & Mining', 'Multi-Utilities',\n", " 'Oil, Gas & Consumable Fuels', 'Paper & Forest Products',\n", " 'Pharmaceuticals', 'Professional Services',\n", " 'Real Estate Management & Development', 'Road & Rail',\n", " 'Semiconductors & Semiconductor Equipment', 'Software',\n", " 'Specialty Retail', 'Technology Hardware, Storage & Peripherals',\n", " 'Textiles, Apparel & Luxury Goods', 'Thrifts & Mortgage Finance',\n", " 'Tobacco', 'Trading Companies & Distributors',\n", " 'Transportation Infrastructure', 'Water Utilities'], dtype=object),\n", " 'exchange': array(['AMS', 'AQS', 'ASE', 'ASX', 'ATH', 'BER', 'BRU', 'BSE', 'BTS',\n", " 'BUD', 'BUE', 'CAI', 'CCS', 'CNQ', 'CPH', 'CSE', 'DOH', 'DUS',\n", " 'EBS', 'ENX', 'FKA', 'FRA', 'GER', 'HAM', 'HAN', 'HEL', 'HKG',\n", " 'ICE', 'IOB', 'ISE', 'IST', 'JKT', 'JNB', 'JPX', 'KLS', 'KOE',\n", " 'KSC', 'LIS', 'LIT', 'LSE', 'MCE', 'MCX', 'MEX', 'MIL', 'MUN',\n", " 'NAE', 'NAS', 'NCM', 'NEO', 'NGM', 'NMS', 'NSE', 'NSI', 'NYQ',\n", " 'NYS', 'NZE', 'OBB', 'OSL', 'PAR', 'PCX', 'PNK', 'PRA', 'RIS',\n", " 'SAO', 'SAP', 'SAT', 'SAU', 'SES', 'SET', 'SGO', 'SHH', 'SHZ',\n", " 'STO', 'STU', 'TAI', 'TAL', 'TLO', 'TLV', 'TOR', 'TWO', 'VAN',\n", " 'VIE'], dtype=object),\n", " 'market': array(['Aequitas NEO Exchange (Lit Book)', 'Aktie Torget',\n", " 'Aquis Exchange', 'Athens Stock Exchange',\n", " 'Australian Securities Exchange', 'BATS BZX Exchange', 'BSE India',\n", " 'BX Worldcaps', 'Berlin Stock Exchange',\n", " 'Bolsa De Valores De Caracas',\n", " 'Bolsa de Comercio de Santiago de Chile', 'Borsa Istanbul',\n", " 'Borsa Italiana', 'Bovespa Soma', 'Budapest Stock Exchange',\n", " 'Buenos Aires Mercato De Valores', 'Bursa Malaysia',\n", " 'Canadian Securities Exchange', 'Dusseldorf Stock Exchange',\n", " 'Egyptian Exchange', 'EuroTLX', 'Euronext', 'Euronext Amsterdam',\n", " 'Euronext Brussels', 'Euronext Lisbon', 'Euronext Paris',\n", " 'First North Copenhagen', 'First North Iceland',\n", " 'Frankfurt Stock Exchange', 'Fukuoka Stock Exchange',\n", " 'Hamburg Stock Exchange', 'Hanover Stock Exchange',\n", " 'Hong Kong Stock Exchange', 'Indonesia Stock Exchange',\n", " 'Irish Stock Exchange', 'Johannesburg Stock Exchange', 'KONEX',\n", " 'KOSPI Stock Market', 'London Stock Exchange (OTC and ITR)',\n", " 'London Stock Exchange (international)',\n", " 'Metropolitan Stock Exchange', 'Mexico Stock Exchange',\n", " 'Moscow Exchange - MICEX', 'Munich Stock Exchange',\n", " 'NASDAQ Capital Market', 'NASDAQ Global Select',\n", " 'NASDAQ OMX Helsinki', 'NASDAQ OMX Riga', 'NASDAQ OMX Stockholm',\n", " 'NASDAQ OMX Tallinn', 'NASDAQ OMX Vilnius', 'NYSE Arca',\n", " 'NYSE MKT', 'Nasdaq Copenhagen',\n", " 'National Stock Exchange of India', 'New York Stock Exchange',\n", " 'New Zealand Exchange', 'Nordic Growth Market',\n", " 'OTC Bulletin Board', 'Oslo Bors', 'Prague Stock Exchange',\n", " 'Qatar Exchange', 'Sapporo Securities Exchange',\n", " 'Saudi Arabian Stock Exchange', 'Shanghai Stock Exchange',\n", " 'Shenzhen Stock Exchange', 'Singapore Exchange',\n", " 'Sociedad de Bolsas (SIBE)', 'Stuttgart Stock Exchange',\n", " 'TSX Toronto Exchange', 'TSX Venture Exchange',\n", " 'Taiwan Stock Exchange', 'Tel Aviv Stock Exchange',\n", " 'The Stock Exchange of Thailand', 'Tokyo Stock Exchange',\n", " 'Vienna Stock Exchange', 'XETRA', 'us24_market', 'us_market'],\n", " dtype=object),\n", " 'country': array(['Afghanistan', 'Anguilla', 'Argentina', 'Australia', 'Austria',\n", " 'Azerbaijan', 'Bahamas', 'Bangladesh', 'Barbados', 'Belgium',\n", " 'Belize', 'Bermuda', 'Botswana', 'Brazil',\n", " 'British Virgin Islands', 'Cambodia', 'Canada', 'Cayman Islands',\n", " 'Chile', 'China', 'Colombia', 'Costa Rica', 'Cyprus',\n", " 'Czech Republic', 'Denmark', 'Dominican Republic', 'Egypt',\n", " 'Estonia', 'Falkland Islands', 'Finland', 'France',\n", " 'French Guiana', 'Gabon', 'Georgia', 'Germany', 'Ghana',\n", " 'Gibraltar', 'Greece', 'Greenland', 'Guernsey', 'Hong Kong',\n", " 'Hungary', 'Iceland', 'India', 'Indonesia', 'Ireland',\n", " 'Isle of Man', 'Israel', 'Italy', 'Ivory Coast', 'Japan', 'Jersey',\n", " 'Jordan', 'Kazakhstan', 'Kenya', 'Kyrgyzstan', 'Latvia',\n", " 'Liechtenstein', 'Lithuania', 'Luxembourg', 'Macau', 'Macedonia',\n", " 'Malaysia', 'Malta', 'Mauritius', 'Mexico', 'Monaco', 'Mongolia',\n", " 'Montenegro', 'Morocco', 'Mozambique', 'Myanmar', 'Namibia',\n", " 'Netherlands', 'Netherlands Antilles', 'New Zealand', 'Nigeria',\n", " 'Norway', 'Panama', 'Papua New Guinea', 'Peru', 'Philippines',\n", " 'Poland', 'Portugal', 'Qatar', 'Reunion', 'Romania', 'Russia',\n", " 'Saudi Arabia', 'Senegal', 'Singapore', 'Slovakia', 'Slovenia',\n", " 'South Africa', 'South Korea', 'Spain', 'Suriname', 'Sweden',\n", " 'Switzerland', 'Taiwan', 'Tanzania', 'Thailand', 'Turkey',\n", " 'Ukraine', 'United Arab Emirates', 'United Kingdom',\n", " 'United States', 'Uruguay', 'Vietnam', 'Zambia'], dtype=object),\n", " 'state': array(['AB', 'ACT', 'AK', 'AL', 'AM', 'AN', 'AP', 'AR', 'AV', 'AZ', 'BA',\n", " 'BC', 'BG', 'BI', 'BJ', 'BL', 'BO', 'BS', 'CA', 'CE', 'CI', 'CO',\n", " 'CT', 'CU', 'DC', 'DE', 'DF', 'EM', 'ES', 'FE', 'FI', 'FL', 'FO',\n", " 'FR', 'GA', 'GE', 'GJ', 'GO', 'GU', 'Gujarat', 'HI', 'IA', 'ID',\n", " 'IL', 'IN', 'JA', 'KS', 'KY', 'LA', 'LC', 'LT', 'LU', 'MA', 'MB',\n", " 'MD', 'ME', 'MG', 'MH', 'MI', 'MN', 'MO', 'MS', 'MT', 'NB', 'NC',\n", " 'ND', 'NE', 'NF', 'NH', 'NJ', 'NL', 'NM', 'NS', 'NSW', 'NT', 'NU',\n", " 'NV', 'NY', 'OH', 'OK', 'ON', 'OR', 'PA', 'PD', 'PE', 'PG', 'PI',\n", " 'PR', 'PS', 'PV', 'QC', 'QLD', 'QR', 'RA', 'RE', 'RI', 'RJ', 'RM',\n", " 'RN', 'RS', 'SA', 'SC', 'SD', 'SE', 'SI', 'SK', 'SO', 'SP', 'TAS',\n", " 'TN', 'TO', 'TR', 'TS', 'TV', 'TX', 'UD', 'UT', 'VA', 'VC', 'VE',\n", " 'VI', 'VIC', 'VR', 'VT', 'WA', 'WI', 'WV', 'WY', 'YT'],\n", " dtype=object),\n", " 'city': array([\"'s-Hertogenbosch\", '6th of October', 'Aabenraa', ...,\n", " 'a€˜s-Hertogenbosch', 'tacheng', 'Ílhavo'],\n", " shape=(5724,), dtype=object),\n", " 'zipcode': array(['00-105', '00-116', '00-124', ..., 'YO8 8PH', 'Z05T1X3', 'v4B 3L1'],\n", " shape=(16277,), dtype=object),\n", " 'market_cap': array(['Large Cap', 'Mega Cap', 'Micro Cap', 'Mid Cap', 'Nano Cap',\n", " 'Small Cap'], dtype=object),\n", " 'isin': array(['AN8068571086', 'ANN4327C1220', 'AT000000STR1', ...,\n", " 'ZAE000265971', 'ZAE000296554', 'ZAE000298253'],\n", " shape=(8961,), dtype=object),\n", " 'cusip': array(['00089H106', '00090Q103', '00108J109', ..., '99406100', '99501108',\n", " '99502106'], shape=(2459,), dtype=object),\n", " 'figi': array(['#REF!', 'BBG000B9XKF0', 'BBG000B9XZV9', ..., 'BBG01FC8CFV3',\n", " 'BBG01FPC3G48', 'BBG01FRH5MP7'], shape=(25103,), dtype=object),\n", " 'composite_figi': array(['BBG000B9WX45', 'BBG000B9XG87', 'BBG000B9XRY4', ...,\n", " 'BBG01FC8CFN2', 'BBG01FP5R015', 'BBG01FRH5MK2'],\n", " shape=(12389,), dtype=object),\n", " 'shareclass_figi': array(['BBG001S112S8', 'BBG001S112X2', 'BBG001S112Y1', ...,\n", " 'BBG01CCBKDK1', 'BBG01FP5R033', 'BBG01FRH5ND8'],\n", " shape=(7463,), dtype=object)}" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Obtain all possible options for equities\n", "fd.show_options(\"equities\")" ] }, { "cell_type": "markdown", "id": "0a0b5978", "metadata": {}, "source": [ "As the equities database has already been loaded in, it is also possible to use a similar functionality from within the class as follows. The main difference is that this functionality allows you to see the options based on a specific filtering. For example." ] }, { "cell_type": "code", "execution_count": 4, "id": "397db95a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'currency': array(['ARS', 'AUD', 'BRL', 'CHF', 'CZK', 'EUR', 'GBP', 'ILA', 'MXN',\n", " 'NOK', 'RUB', 'USD', 'ZAC'], dtype=object),\n", " 'sector': array(['Communication Services', 'Consumer Discretionary',\n", " 'Consumer Staples', 'Energy', 'Financials', 'Health Care',\n", " 'Industrials', 'Information Technology', 'Materials',\n", " 'Real Estate', 'Utilities'], dtype=object),\n", " 'industry_group': array(['Automobiles & Components', 'Banks', 'Capital Goods',\n", " 'Commercial & Professional Services',\n", " 'Consumer Durables & Apparel', 'Consumer Services',\n", " 'Diversified Financials', 'Energy', 'Food & Staples Retailing',\n", " 'Food, Beverage & Tobacco', 'Health Care Equipment & Services',\n", " 'Household & Personal Products', 'Insurance', 'Materials',\n", " 'Media & Entertainment',\n", " 'Pharmaceuticals, Biotechnology & Life Sciences', 'Real Estate',\n", " 'Retailing', 'Semiconductors & Semiconductor Equipment',\n", " 'Software & Services', 'Technology Hardware & Equipment',\n", " 'Telecommunication Services', 'Transportation', 'Utilities'],\n", " dtype=object),\n", " 'industry': array(['Aerospace & Defense', 'Air Freight & Logistics', 'Airlines',\n", " 'Auto Components', 'Automobiles', 'Banks', 'Beverages',\n", " 'Biotechnology', 'Building Products', 'Capital Markets',\n", " 'Chemicals', 'Commercial Services & Supplies',\n", " 'Communications Equipment', 'Construction & Engineering',\n", " 'Consumer Finance', 'Diversified Financial Services',\n", " 'Diversified Telecommunication Services', 'Electrical Equipment',\n", " 'Electronic Equipment, Instruments & Components',\n", " 'Energy Equipment & Services',\n", " 'Equity Real Estate Investment Trusts (REITs)',\n", " 'Food & Staples Retailing', 'Health Care Equipment & Supplies',\n", " 'Hotels, Restaurants & Leisure', 'Household Durables',\n", " 'Household Products', 'IT Services',\n", " 'Independent Power and Renewable Electricity Producers',\n", " 'Insurance', 'Interactive Media & Services',\n", " 'Internet & Direct Marketing Retail', 'Machinery',\n", " 'Metals & Mining', 'Oil, Gas & Consumable Fuels',\n", " 'Pharmaceuticals', 'Professional Services',\n", " 'Real Estate Management & Development',\n", " 'Semiconductors & Semiconductor Equipment', 'Software',\n", " 'Specialty Retail', 'Technology Hardware, Storage & Peripherals',\n", " 'Textiles, Apparel & Luxury Goods'], dtype=object),\n", " 'exchange': array(['AMS', 'ASE', 'ASX', 'BER', 'BRU', 'BUE', 'DUS', 'EBS', 'FRA',\n", " 'GER', 'HAM', 'HAN', 'IOB', 'JNB', 'LSE', 'MCE', 'MCX', 'MEX',\n", " 'MIL', 'MUN', 'NCM', 'NGM', 'NMS', 'NYQ', 'OSL', 'PAR', 'PNK',\n", " 'PRA', 'SAO', 'STU', 'TLO', 'TLV', 'VIE'], dtype=object),\n", " 'market': array(['Australian Securities Exchange', 'BX Worldcaps',\n", " 'Berlin Stock Exchange', 'Borsa Italiana', 'Bovespa Soma',\n", " 'Buenos Aires Mercato De Valores', 'Dusseldorf Stock Exchange',\n", " 'EuroTLX', 'Euronext Amsterdam', 'Euronext Brussels',\n", " 'Euronext Paris', 'Frankfurt Stock Exchange',\n", " 'Hamburg Stock Exchange', 'Hanover Stock Exchange',\n", " 'Johannesburg Stock Exchange',\n", " 'London Stock Exchange (OTC and ITR)',\n", " 'London Stock Exchange (international)', 'Mexico Stock Exchange',\n", " 'Moscow Exchange - MICEX', 'Munich Stock Exchange',\n", " 'NASDAQ Capital Market', 'NASDAQ Global Select', 'NYSE MKT',\n", " 'New York Stock Exchange', 'Nordic Growth Market',\n", " 'OTC Bulletin Board', 'Oslo Bors', 'Prague Stock Exchange',\n", " 'Sociedad de Bolsas (SIBE)', 'Stuttgart Stock Exchange',\n", " 'Tel Aviv Stock Exchange', 'Vienna Stock Exchange', 'XETRA'],\n", " dtype=object),\n", " 'country': array(['Netherlands'], dtype=object),\n", " 'market_cap': array(['Large Cap', 'Mega Cap', 'Micro Cap', 'Mid Cap', 'Nano Cap',\n", " 'Small Cap'], dtype=object)}" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.show_options(country=\"Netherlands\")" ] }, { "cell_type": "markdown", "id": "160a9974", "metadata": {}, "source": [ "Or only showing one specific parameter." ] }, { "cell_type": "code", "execution_count": 5, "id": "e056a632", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Banks', 'Capital Markets', 'Consumer Finance',\n", " 'Diversified Financial Services', 'Insurance'], dtype=object)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.show_options(\n", " selection=\"industry\",\n", " sector=\"Financials\",\n", " country=\"Netherlands\")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "99032b0f", "metadata": {}, "source": [ "Given this information, it then becomes possible to filter the database based on the parameters you are interested in. For example, if you are interested 'Insurance' companies in the 'Netherlands' you can use the following. Note that I ommit the `sector` here, given that the selection I make is on a deeper level and therefore it is a given that the sector is 'Financials'." ] }, { "cell_type": "code", "execution_count": 6, "id": "735ec31b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namesummarycurrencysectorindustry_groupindustryexchangemarketcountrystatecityzipcodewebsitemarket_capisincusipfigicomposite_figishareclass_figi
symbol
A16.FASR Nederland N.V.ASR Nederland N.V. provides various insurance ...EURFinancialsInsuranceInsuranceFRAFrankfurt Stock ExchangeNetherlandsNaNUtrecht3584 BAhttp://www.asrnl.comMid CapNL0011872643NaNBBG00D2VFV96BBG00D2VFV78BBG00CWZ0HK0
A1EG34.SAAegon N.V.Aegon N.V. provides a range of financial servi...BRLFinancialsInsuranceInsuranceSAOBovespa SomaNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNNaNNaNNaN
AEGAegon N.V.Aegon N.V. provides a range of financial servi...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comLarge CapNL0000303709NaNBBG000CKQTN4BBG000CKQSN6BBG001S6Y6M8
AEGOFAegon N.V.Aegon N.V. provides a range of financial servi...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNNaNNaNNaN
AEND.DEAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceGERXETRANetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000DJK260BBG000DJHZF1BBG001S5V8R4
AEND.FAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceFRAFrankfurt Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000DJJ002BBG000DJHZF1BBG001S5V8R4
AEND.SGAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceSTUStuttgart Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000DJK2M2BBG000DJHZF1BBG001S5V8R4
AENF.DEAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceGERXETRANetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNNaNNaNNaN
AENF.FAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceFRAFrankfurt Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000PQ4D38BBG000PQ4CB1BBG001S6Y6M8
AENF.SGAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceSTUStuttgart Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000PQ4FQ8BBG000PQ4CB1BBG001S6Y6M8
AGN.ASAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceAMSEuronext AmsterdamNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000JN9DM6BBG000JN9C93BBG001S5V8R4
AGN.MIAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceMILBorsa ItalianaNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000MJVT05BBG000MJVSD3BBG001S5V8R4
AGN.VIAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceVIEVienna Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG00HVY3GH6BBG00HVY3GG7BBG001S5V8R4
ASRNL.ASASR Nederland N.V.ASR Nederland N.V. provides various insurance ...EURFinancialsInsuranceInsuranceAMSEuronext AmsterdamNetherlandsNaNUtrecht3584 BAhttp://www.asrnl.comMid CapNL0011872643NaNBBG00CWZ0HG5BBG00CWZ0HF6BBG00CWZ0HK0
NN.ASNN Group N.V.NN Group N.V., a financial services company, p...EURFinancialsInsuranceInsuranceAMSEuronext AmsterdamNetherlandsNaNThe Hague2595 AShttp://www.nn-group.comLarge CapNaNNaNNaNNaNNaN
NN.VINN Group N.V.NN Group N.V., a financial services company, p...EURFinancialsInsuranceInsuranceVIEVienna Stock ExchangeNetherlandsNaNThe Hague2595 AShttp://www.nn-group.comLarge CapNaNNaNNaNNaNNaN
NNGPFNN Group N.V.NN Group N.V., a financial services company, p...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardNetherlandsNaNThe Hague2595 AShttp://www.nn-group.comLarge CapNaNNaNNaNNaNNaN
NNGRYNN Group N.V.NN Group N.V., a financial services company, p...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardNetherlandsNaNThe Hague2595 AShttp://www.nn-group.comLarge CapNaNNaNNaNNaNNaN
\n", "
" ], "text/plain": [ " name \\\n", "symbol \n", "A16.F ASR Nederland N.V. \n", "A1EG34.SA Aegon N.V. \n", "AEG Aegon N.V. \n", "AEGOF Aegon N.V. \n", "AEND.DE Aegon N.V. \n", "AEND.F Aegon N.V. \n", "AEND.SG Aegon N.V. \n", "AENF.DE Aegon N.V. \n", "AENF.F Aegon N.V. \n", "AENF.SG Aegon N.V. \n", "AGN.AS Aegon N.V. \n", "AGN.MI Aegon N.V. \n", "AGN.VI Aegon N.V. \n", "ASRNL.AS ASR Nederland N.V. \n", "NN.AS NN Group N.V. \n", "NN.VI NN Group N.V. \n", "NNGPF NN Group N.V. \n", "NNGRY NN Group N.V. \n", "\n", " summary currency \\\n", "symbol \n", "A16.F ASR Nederland N.V. provides various insurance ... EUR \n", "A1EG34.SA Aegon N.V. provides a range of financial servi... BRL \n", "AEG Aegon N.V. provides a range of financial servi... USD \n", "AEGOF Aegon N.V. provides a range of financial servi... USD \n", "AEND.DE Aegon N.V. provides a range of financial servi... EUR \n", "AEND.F Aegon N.V. provides a range of financial servi... EUR \n", "AEND.SG Aegon N.V. provides a range of financial servi... EUR \n", "AENF.DE Aegon N.V. provides a range of financial servi... EUR \n", "AENF.F Aegon N.V. provides a range of financial servi... EUR \n", "AENF.SG Aegon N.V. provides a range of financial servi... EUR \n", "AGN.AS Aegon N.V. provides a range of financial servi... EUR \n", "AGN.MI Aegon N.V. provides a range of financial servi... EUR \n", "AGN.VI Aegon N.V. provides a range of financial servi... EUR \n", "ASRNL.AS ASR Nederland N.V. provides various insurance ... EUR \n", "NN.AS NN Group N.V., a financial services company, p... EUR \n", "NN.VI NN Group N.V., a financial services company, p... EUR \n", "NNGPF NN Group N.V., a financial services company, p... USD \n", "NNGRY NN Group N.V., a financial services company, p... USD \n", "\n", " sector industry_group industry exchange \\\n", "symbol \n", "A16.F Financials Insurance Insurance FRA \n", "A1EG34.SA Financials Insurance Insurance SAO \n", "AEG Financials Insurance Insurance NYQ \n", "AEGOF Financials Insurance Insurance PNK \n", "AEND.DE Financials Insurance Insurance GER \n", "AEND.F Financials Insurance Insurance FRA \n", "AEND.SG Financials Insurance Insurance STU \n", "AENF.DE Financials Insurance Insurance GER \n", "AENF.F Financials Insurance Insurance FRA \n", "AENF.SG Financials Insurance Insurance STU \n", "AGN.AS Financials Insurance Insurance AMS \n", "AGN.MI Financials Insurance Insurance MIL \n", "AGN.VI Financials Insurance Insurance VIE \n", "ASRNL.AS Financials Insurance Insurance AMS \n", "NN.AS Financials Insurance Insurance AMS \n", "NN.VI Financials Insurance Insurance VIE \n", "NNGPF Financials Insurance Insurance PNK \n", "NNGRY Financials Insurance Insurance PNK \n", "\n", " market country state city zipcode \\\n", "symbol \n", "A16.F Frankfurt Stock Exchange Netherlands NaN Utrecht 3584 BA \n", "A1EG34.SA Bovespa Soma Netherlands NaN The Hague 2591 TV \n", "AEG New York Stock Exchange Netherlands NaN The Hague 2591 TV \n", "AEGOF OTC Bulletin Board Netherlands NaN The Hague 2591 TV \n", "AEND.DE XETRA Netherlands NaN The Hague 2591 TV \n", "AEND.F Frankfurt Stock Exchange Netherlands NaN The Hague 2591 TV \n", "AEND.SG Stuttgart Stock Exchange Netherlands NaN The Hague 2591 TV \n", "AENF.DE XETRA Netherlands NaN The Hague 2591 TV \n", "AENF.F Frankfurt Stock Exchange Netherlands NaN The Hague 2591 TV \n", "AENF.SG Stuttgart Stock Exchange Netherlands NaN The Hague 2591 TV \n", "AGN.AS Euronext Amsterdam Netherlands NaN The Hague 2591 TV \n", "AGN.MI Borsa Italiana Netherlands NaN The Hague 2591 TV \n", "AGN.VI Vienna Stock Exchange Netherlands NaN The Hague 2591 TV \n", "ASRNL.AS Euronext Amsterdam Netherlands NaN Utrecht 3584 BA \n", "NN.AS Euronext Amsterdam Netherlands NaN The Hague 2595 AS \n", "NN.VI Vienna Stock Exchange Netherlands NaN The Hague 2595 AS \n", "NNGPF OTC Bulletin Board Netherlands NaN The Hague 2595 AS \n", "NNGRY OTC Bulletin Board Netherlands NaN The Hague 2595 AS \n", "\n", " website market_cap isin cusip \\\n", "symbol \n", "A16.F http://www.asrnl.com Mid Cap NL0011872643 NaN \n", "A1EG34.SA http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AEG http://www.aegon.com Large Cap NL0000303709 NaN \n", "AEGOF http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AEND.DE http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AEND.F http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AEND.SG http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AENF.DE http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AENF.F http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AENF.SG http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AGN.AS http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AGN.MI http://www.aegon.com Mid Cap NL0000303709 NaN \n", "AGN.VI http://www.aegon.com Mid Cap NL0000303709 NaN \n", "ASRNL.AS http://www.asrnl.com Mid Cap NL0011872643 NaN \n", "NN.AS http://www.nn-group.com Large Cap NaN NaN \n", "NN.VI http://www.nn-group.com Large Cap NaN NaN \n", "NNGPF http://www.nn-group.com Large Cap NaN NaN \n", "NNGRY http://www.nn-group.com Large Cap NaN NaN \n", "\n", " figi composite_figi shareclass_figi \n", "symbol \n", "A16.F BBG00D2VFV96 BBG00D2VFV78 BBG00CWZ0HK0 \n", "A1EG34.SA NaN NaN NaN \n", "AEG BBG000CKQTN4 BBG000CKQSN6 BBG001S6Y6M8 \n", "AEGOF NaN NaN NaN \n", "AEND.DE BBG000DJK260 BBG000DJHZF1 BBG001S5V8R4 \n", "AEND.F BBG000DJJ002 BBG000DJHZF1 BBG001S5V8R4 \n", "AEND.SG BBG000DJK2M2 BBG000DJHZF1 BBG001S5V8R4 \n", "AENF.DE NaN NaN NaN \n", "AENF.F BBG000PQ4D38 BBG000PQ4CB1 BBG001S6Y6M8 \n", "AENF.SG BBG000PQ4FQ8 BBG000PQ4CB1 BBG001S6Y6M8 \n", "AGN.AS BBG000JN9DM6 BBG000JN9C93 BBG001S5V8R4 \n", "AGN.MI BBG000MJVT05 BBG000MJVSD3 BBG001S5V8R4 \n", "AGN.VI BBG00HVY3GH6 BBG00HVY3GG7 BBG001S5V8R4 \n", "ASRNL.AS BBG00CWZ0HG5 BBG00CWZ0HF6 BBG00CWZ0HK0 \n", "NN.AS NaN NaN NaN \n", "NN.VI NaN NaN NaN \n", "NNGPF NaN NaN NaN \n", "NNGRY NaN NaN NaN " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.select(\n", " country=\"Netherlands\",\n", " industry=\"Insurance\",\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "6ae6fb1d", "metadata": {}, "source": [ "You'll see that the same company can appear multiple times. This is because by default all exchanges are shown. There are two methods to focus on one entry:\n", "\n", "- Use the `only_primary_listing` parameter. This will only show the primary listing of each company. This is useful mostly if you are looking into the US exchanges.\n", "- Use the `exchange` or `market` parameter. This will allow you to filter on a specific exchange or market. This is useful when you not neccesarily looking into US exchanges and are already filtering on a specific country.\n", "\n", "For example, filtering on the Netherlands it makes sense to select a Dutch exchange as well. This is for example the exchange \"AMS\" or the market \"Euronext Amsterdam\". This will already give you a much smaller selection." ] }, { "cell_type": "code", "execution_count": 7, "id": "d56a5e98", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namesummarycurrencysectorindustry_groupindustryexchangemarketcountrystatecityzipcodewebsitemarket_capisincusipfigicomposite_figishareclass_figi
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AGN.ASAegon N.V.Aegon N.V. provides a range of financial servi...EURFinancialsInsuranceInsuranceAMSEuronext AmsterdamNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNBBG000JN9DM6BBG000JN9C93BBG001S5V8R4
ASRNL.ASASR Nederland N.V.ASR Nederland N.V. provides various insurance ...EURFinancialsInsuranceInsuranceAMSEuronext AmsterdamNetherlandsNaNUtrecht3584 BAhttp://www.asrnl.comMid CapNL0011872643NaNBBG00CWZ0HG5BBG00CWZ0HF6BBG00CWZ0HK0
NN.ASNN Group N.V.NN Group N.V., a financial services company, p...EURFinancialsInsuranceInsuranceAMSEuronext AmsterdamNetherlandsNaNThe Hague2595 AShttp://www.nn-group.comLarge CapNaNNaNNaNNaNNaN
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" ], "text/plain": [ " name \\\n", "symbol \n", "AGN.AS Aegon N.V. \n", "ASRNL.AS ASR Nederland N.V. \n", "NN.AS NN Group N.V. \n", "\n", " summary currency \\\n", "symbol \n", "AGN.AS Aegon N.V. provides a range of financial servi... EUR \n", "ASRNL.AS ASR Nederland N.V. provides various insurance ... EUR \n", "NN.AS NN Group N.V., a financial services company, p... EUR \n", "\n", " sector industry_group industry exchange market \\\n", "symbol \n", "AGN.AS Financials Insurance Insurance AMS Euronext Amsterdam \n", "ASRNL.AS Financials Insurance Insurance AMS Euronext Amsterdam \n", "NN.AS Financials Insurance Insurance AMS Euronext Amsterdam \n", "\n", " country state city zipcode website \\\n", "symbol \n", "AGN.AS Netherlands NaN The Hague 2591 TV http://www.aegon.com \n", "ASRNL.AS Netherlands NaN Utrecht 3584 BA http://www.asrnl.com \n", "NN.AS Netherlands NaN The Hague 2595 AS http://www.nn-group.com \n", "\n", " market_cap isin cusip figi composite_figi \\\n", "symbol \n", "AGN.AS Mid Cap NL0000303709 NaN BBG000JN9DM6 BBG000JN9C93 \n", "ASRNL.AS Mid Cap NL0011872643 NaN BBG00CWZ0HG5 BBG00CWZ0HF6 \n", "NN.AS Large Cap NaN NaN NaN NaN \n", "\n", " shareclass_figi \n", "symbol \n", "AGN.AS BBG001S5V8R4 \n", "ASRNL.AS BBG00CWZ0HK0 \n", "NN.AS NaN " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.select(\n", " country=\"Netherlands\",\n", " industry=\"Insurance\",\n", " market=\"Euronext Amsterdam\",\n", ")" ] }, { "cell_type": "markdown", "id": "76cd189f", "metadata": {}, "source": [ "Given that the Netherlands is a relatively small country, it is not uncommon for the list to become small quick. For example, the same selection for the United States is already much larger, also utilizing the `only_primary_listing` parameter." ] }, { "cell_type": "code", "execution_count": 8, "id": "0dec592b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namesummarycurrencysectorindustry_groupindustryexchangemarketcountrystatecityzipcodewebsitemarket_capisincusipfigicomposite_figishareclass_figi
symbol
AAMEAtlantic American CorporationAtlantic American Corporation, through its sub...USDFinancialsInsuranceInsuranceNGMNordic Growth MarketUnited StatesGAAtlanta30319-3054http://www.atlam.comNano CapNaNNaNNaNNaNNaN
ACMTACMAT CorporationACMAT Corporation, through its subsidiary, ACS...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardUnited StatesCTFarmington6032http://www.acmatcorp.comNano CapNaNNaNNaNNaNNaN
ACMTAACMAT CorporationACMAT Corporation, through its subsidiary, ACS...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardUnited StatesCTFarmington6032http://www.acmatcorp.comNano CapNaNNaNNaNNaNNaN
AELAmerican Equity Investment Life Holding CompanyAmerican Equity Investment Life Holding Compan...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesIAWest Des Moines50266http://www.american-equity.comMid CapNaNNaNNaNNaNNaN
AEL-PAAmerican Equity Investment Life Holding CompanyAmerican Equity Investment Life Holding Compan...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesIAWest Des Moines50266http://www.american-equity.comMid CapNaNNaNNaNNaNNaN
............................................................
VERYVericity, Inc.Vericity, Inc., together with its subsidiaries...USDFinancialsInsuranceInsuranceNCMNASDAQ Capital MarketUnited StatesILChicago60631http://www.vericity.comMicro CapUS92347D100092347D100BBG00PC36SH8BBG00PC36S42BBG00PC36SW1
WRBW. R. Berkley CorporationW. R. Berkley Corporation, an insurance holdin...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesCTGreenwich6830http://www.berkley.comLarge CapNaNNaNBBG000BD1KV8BBG000BD1HP2BBG001S5P463
WRB-PDW. R. Berkley CorporationW. R. Berkley Corporation, an insurance holdin...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesCTGreenwich6830http://www.berkley.comLarge CapNaNNaNNaNNaNNaN
WRB-PEW. R. Berkley CorporationW. R. Berkley Corporation, an insurance holdin...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesCTGreenwich6830http://www.berkley.comLarge CapNaNNaNNaNNaNNaN
YAlleghany CorporationAlleghany Corporation provides property and ca...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesNYNew York10018http://www.alleghany.comLarge CapNaNNaNNaNNaNNaN
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168 rows × 19 columns

\n", "
" ], "text/plain": [ " name \\\n", "symbol \n", "AAME Atlantic American Corporation \n", "ACMT ACMAT Corporation \n", "ACMTA ACMAT Corporation \n", "AEL American Equity Investment Life Holding Company \n", "AEL-PA American Equity Investment Life Holding Company \n", "... ... \n", "VERY Vericity, Inc. \n", "WRB W. R. Berkley Corporation \n", "WRB-PD W. R. Berkley Corporation \n", "WRB-PE W. R. Berkley Corporation \n", "Y Alleghany Corporation \n", "\n", " summary currency \\\n", "symbol \n", "AAME Atlantic American Corporation, through its sub... USD \n", "ACMT ACMAT Corporation, through its subsidiary, ACS... USD \n", "ACMTA ACMAT Corporation, through its subsidiary, ACS... USD \n", "AEL American Equity Investment Life Holding Compan... USD \n", "AEL-PA American Equity Investment Life Holding Compan... USD \n", "... ... ... \n", "VERY Vericity, Inc., together with its subsidiaries... USD \n", "WRB W. R. Berkley Corporation, an insurance holdin... USD \n", "WRB-PD W. R. Berkley Corporation, an insurance holdin... USD \n", "WRB-PE W. R. Berkley Corporation, an insurance holdin... USD \n", "Y Alleghany Corporation provides property and ca... USD \n", "\n", " sector industry_group industry exchange \\\n", "symbol \n", "AAME Financials Insurance Insurance NGM \n", "ACMT Financials Insurance Insurance PNK \n", "ACMTA Financials Insurance Insurance PNK \n", "AEL Financials Insurance Insurance NYQ \n", "AEL-PA Financials Insurance Insurance NYQ \n", "... ... ... ... ... \n", "VERY Financials Insurance Insurance NCM \n", "WRB Financials Insurance Insurance NYQ \n", "WRB-PD Financials Insurance Insurance NYQ \n", "WRB-PE Financials Insurance Insurance NYQ \n", "Y Financials Insurance Insurance NYQ \n", "\n", " market country state city \\\n", "symbol \n", "AAME Nordic Growth Market United States GA Atlanta \n", "ACMT OTC Bulletin Board United States CT Farmington \n", "ACMTA OTC Bulletin Board United States CT Farmington \n", "AEL New York Stock Exchange United States IA West Des Moines \n", "AEL-PA New York Stock Exchange United States IA West Des Moines \n", "... ... ... ... ... \n", "VERY NASDAQ Capital Market United States IL Chicago \n", "WRB New York Stock Exchange United States CT Greenwich \n", "WRB-PD New York Stock Exchange United States CT Greenwich \n", "WRB-PE New York Stock Exchange United States CT Greenwich \n", "Y New York Stock Exchange United States NY New York \n", "\n", " zipcode website market_cap isin \\\n", "symbol \n", "AAME 30319-3054 http://www.atlam.com Nano Cap NaN \n", "ACMT 6032 http://www.acmatcorp.com Nano Cap NaN \n", "ACMTA 6032 http://www.acmatcorp.com Nano Cap NaN \n", "AEL 50266 http://www.american-equity.com Mid Cap NaN \n", "AEL-PA 50266 http://www.american-equity.com Mid Cap NaN \n", "... ... ... ... ... \n", "VERY 60631 http://www.vericity.com Micro Cap US92347D1000 \n", "WRB 6830 http://www.berkley.com Large Cap NaN \n", "WRB-PD 6830 http://www.berkley.com Large Cap NaN \n", "WRB-PE 6830 http://www.berkley.com Large Cap NaN \n", "Y 10018 http://www.alleghany.com Large Cap NaN \n", "\n", " cusip figi composite_figi shareclass_figi \n", "symbol \n", "AAME NaN NaN NaN NaN \n", "ACMT NaN NaN NaN NaN \n", "ACMTA NaN NaN NaN NaN \n", "AEL NaN NaN NaN NaN \n", "AEL-PA NaN NaN NaN NaN \n", "... ... ... ... ... \n", "VERY 92347D100 BBG00PC36SH8 BBG00PC36S42 BBG00PC36SW1 \n", "WRB NaN BBG000BD1KV8 BBG000BD1HP2 BBG001S5P463 \n", "WRB-PD NaN NaN NaN NaN \n", "WRB-PE NaN NaN NaN NaN \n", "Y NaN NaN NaN NaN \n", "\n", "[168 rows x 19 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.select(\n", " country=\"United States\",\n", " industry=\"Insurance\",\n", " only_primary_listing=True\n", ")" ] }, { "cell_type": "markdown", "id": "2a7ff6d1", "metadata": {}, "source": [ "For any of the variables, it is also possible to provide a list instead. Which means that it will return all entries that match any of the variables. As an example, the queries above can be combined into one." ] }, { "cell_type": "code", "execution_count": 9, "id": "7dc89d18", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namesummarycurrencysectorindustry_groupindustryexchangemarketcountrystatecityzipcodewebsitemarket_capisincusipfigicomposite_figishareclass_figi
symbol
AAMEAtlantic American CorporationAtlantic American Corporation, through its sub...USDFinancialsInsuranceInsuranceNGMNordic Growth MarketUnited StatesGAAtlanta30319-3054http://www.atlam.comNano CapNaNNaNNaNNaNNaN
ACMTACMAT CorporationACMAT Corporation, through its subsidiary, ACS...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardUnited StatesCTFarmington6032http://www.acmatcorp.comNano CapNaNNaNNaNNaNNaN
ACMTAACMAT CorporationACMAT Corporation, through its subsidiary, ACS...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardUnited StatesCTFarmington6032http://www.acmatcorp.comNano CapNaNNaNNaNNaNNaN
AEGAegon N.V.Aegon N.V. provides a range of financial servi...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comLarge CapNL0000303709NaNBBG000CKQTN4BBG000CKQSN6BBG001S6Y6M8
AEGOFAegon N.V.Aegon N.V. provides a range of financial servi...USDFinancialsInsuranceInsurancePNKOTC Bulletin BoardNetherlandsNaNThe Hague2591 TVhttp://www.aegon.comMid CapNL0000303709NaNNaNNaNNaN
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VERYVericity, Inc.Vericity, Inc., together with its subsidiaries...USDFinancialsInsuranceInsuranceNCMNASDAQ Capital MarketUnited StatesILChicago60631http://www.vericity.comMicro CapUS92347D100092347D100BBG00PC36SH8BBG00PC36S42BBG00PC36SW1
WRBW. R. Berkley CorporationW. R. Berkley Corporation, an insurance holdin...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesCTGreenwich6830http://www.berkley.comLarge CapNaNNaNBBG000BD1KV8BBG000BD1HP2BBG001S5P463
WRB-PDW. R. Berkley CorporationW. R. Berkley Corporation, an insurance holdin...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesCTGreenwich6830http://www.berkley.comLarge CapNaNNaNNaNNaNNaN
WRB-PEW. R. Berkley CorporationW. R. Berkley Corporation, an insurance holdin...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesCTGreenwich6830http://www.berkley.comLarge CapNaNNaNNaNNaNNaN
YAlleghany CorporationAlleghany Corporation provides property and ca...USDFinancialsInsuranceInsuranceNYQNew York Stock ExchangeUnited StatesNYNew York10018http://www.alleghany.comLarge CapNaNNaNNaNNaNNaN
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175 rows × 19 columns

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" ], "text/plain": [ " name \\\n", "symbol \n", "AAME Atlantic American Corporation \n", "ACMT ACMAT Corporation \n", "ACMTA ACMAT Corporation \n", "AEG Aegon N.V. \n", "AEGOF Aegon N.V. \n", "... ... \n", "VERY Vericity, Inc. \n", "WRB W. R. Berkley Corporation \n", "WRB-PD W. R. Berkley Corporation \n", "WRB-PE W. R. Berkley Corporation \n", "Y Alleghany Corporation \n", "\n", " summary currency \\\n", "symbol \n", "AAME Atlantic American Corporation, through its sub... USD \n", "ACMT ACMAT Corporation, through its subsidiary, ACS... USD \n", "ACMTA ACMAT Corporation, through its subsidiary, ACS... USD \n", "AEG Aegon N.V. provides a range of financial servi... USD \n", "AEGOF Aegon N.V. provides a range of financial servi... USD \n", "... ... ... \n", "VERY Vericity, Inc., together with its subsidiaries... USD \n", "WRB W. R. Berkley Corporation, an insurance holdin... USD \n", "WRB-PD W. R. Berkley Corporation, an insurance holdin... USD \n", "WRB-PE W. R. Berkley Corporation, an insurance holdin... USD \n", "Y Alleghany Corporation provides property and ca... USD \n", "\n", " sector industry_group industry exchange \\\n", "symbol \n", "AAME Financials Insurance Insurance NGM \n", "ACMT Financials Insurance Insurance PNK \n", "ACMTA Financials Insurance Insurance PNK \n", "AEG Financials Insurance Insurance NYQ \n", "AEGOF Financials Insurance Insurance PNK \n", "... ... ... ... ... \n", "VERY Financials Insurance Insurance NCM \n", "WRB Financials Insurance Insurance NYQ \n", "WRB-PD Financials Insurance Insurance NYQ \n", "WRB-PE Financials Insurance Insurance NYQ \n", "Y Financials Insurance Insurance NYQ \n", "\n", " market country state city zipcode \\\n", "symbol \n", "AAME Nordic Growth Market United States GA Atlanta 30319-3054 \n", "ACMT OTC Bulletin Board United States CT Farmington 6032 \n", "ACMTA OTC Bulletin Board United States CT Farmington 6032 \n", "AEG New York Stock Exchange Netherlands NaN The Hague 2591 TV \n", "AEGOF OTC Bulletin Board Netherlands NaN The Hague 2591 TV \n", "... ... ... ... ... ... \n", "VERY NASDAQ Capital Market United States IL Chicago 60631 \n", "WRB New York Stock Exchange United States CT Greenwich 6830 \n", "WRB-PD New York Stock Exchange United States CT Greenwich 6830 \n", "WRB-PE New York Stock Exchange United States CT Greenwich 6830 \n", "Y New York Stock Exchange United States NY New York 10018 \n", "\n", " website market_cap isin cusip \\\n", "symbol \n", "AAME http://www.atlam.com Nano Cap NaN NaN \n", "ACMT http://www.acmatcorp.com Nano Cap NaN NaN \n", "ACMTA http://www.acmatcorp.com Nano Cap NaN NaN \n", "AEG http://www.aegon.com Large Cap NL0000303709 NaN \n", "AEGOF http://www.aegon.com Mid Cap NL0000303709 NaN \n", "... ... ... ... ... \n", "VERY http://www.vericity.com Micro Cap US92347D1000 92347D100 \n", "WRB http://www.berkley.com Large Cap NaN NaN \n", "WRB-PD http://www.berkley.com Large Cap NaN NaN \n", "WRB-PE http://www.berkley.com Large Cap NaN NaN \n", "Y http://www.alleghany.com Large Cap NaN NaN \n", "\n", " figi composite_figi shareclass_figi \n", "symbol \n", "AAME NaN NaN NaN \n", "ACMT NaN NaN NaN \n", "ACMTA NaN NaN NaN \n", "AEG BBG000CKQTN4 BBG000CKQSN6 BBG001S6Y6M8 \n", "AEGOF NaN NaN NaN \n", "... ... ... ... \n", "VERY BBG00PC36SH8 BBG00PC36S42 BBG00PC36SW1 \n", "WRB BBG000BD1KV8 BBG000BD1HP2 BBG001S5P463 \n", "WRB-PD NaN NaN NaN \n", "WRB-PE NaN NaN NaN \n", "Y NaN NaN NaN \n", "\n", "[175 rows x 19 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.select(\n", " country=[\"Netherlands\", \"United States\"],\n", " industry=\"Insurance\",\n", " market=[\"Euronext Amsterdam\", \"Nordic Growth Market\", \"OTC Bulletin Board\",\n", " \"New York Stock Exchange\", \"NASDAQ Global Select\", \"NYSE MKT\",\n", " \"NASDAQ Capital Market\"]\n", ")" ] }, { "cell_type": "markdown", "id": "e7bbf39b", "metadata": {}, "source": [ "In case the current categorization doesn't lead to the results you are looking for, it is possible to use the `search` parameter. This allows you to filter on any column in the database via a custom string. This means that if the word or sentence you input is found somewhere in the column you select, it will return the result. \n", "\n", "By default the result will not be case sensitive but you can adjust this by setting `case_sensitive=True`. You can also filter the index (`symbol` column) by using `index` as shown below. Just like the `select` function, you can also provide lists here." ] }, { "cell_type": "code", "execution_count": 10, "id": "d9b107df", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namesummarycurrencysectorindustry_groupindustryexchangemarketcountrystatecityzipcodewebsitemarket_capisincusipfigicomposite_figishareclass_figi
symbol
109.FCastlight Health, Inc.Castlight Health, Inc. provides health navigat...EURHealth CareHealth Care Equipment & ServicesHealth Care Providers & ServicesFRAFrankfurt Stock ExchangeUnited StatesCASan Francisco94105http://www.castlighthealth.comSmall CapNaNNaNNaNNaNNaN
1KT.FKeysight Technologies, Inc.Keysight Technologies, Inc. provides electroni...EURInformation TechnologyTechnology Hardware & EquipmentElectronic Equipment, Instruments & ComponentsFRAFrankfurt Stock ExchangeUnited StatesCASanta Rosa95403-1738http://www.keysight.comLarge CapUS49338L103549338L103BBG007DJZFD2BBG007DJZFC3BBG0059FN820
1N1.FNanalysis Scientific Corp.Nanalysis Scientific Corp., develops, manufact...EURInformation TechnologyTechnology Hardware & EquipmentElectronic Equipment, Instruments & ComponentsFRAFrankfurt Stock ExchangeCanadaABCalgaryT2E 7C3http://www.nanalysis.comNano CapNaNNaNNaNNaNNaN
1YO.FYangtze Optical Fibre And Cable Joint Stock Li...Yangtze Optical Fibre And Cable Joint Stock Li...EURInformation TechnologyTechnology Hardware & EquipmentCommunications EquipmentFRAFrankfurt Stock ExchangeChinaNaNWuhan430073http://www.yofc.comSmall CapNaNNaNNaNNaNNaN
1ZU.FThe Pennant Group, Inc.The Pennant Group, Inc. provides healthcare se...EURHealth CareHealth Care Equipment & ServicesHealth Care Equipment & SuppliesFRAFrankfurt Stock ExchangeUnited StatesIDEagle83616http://pennantgroup.comSmall CapUS70805E10917.08E+113BBG00QJ35K78BBG00QJ35K69BBG00P33SZ15
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V00.FVocera Communications, Inc.Vocera Communications, Inc. provides secure, i...EURInformation TechnologyTechnology Hardware & EquipmentCommunications EquipmentFRAFrankfurt Stock ExchangeUnited StatesCASan Jose95126http://www.vocera.comSmall CapNaNNaNNaNNaNNaN
VNI.FAvnet, Inc.Avnet, Inc., a technology solutions company, m...EURInformation TechnologyTechnology Hardware & EquipmentElectronic Equipment, Instruments & ComponentsFRAFrankfurt Stock ExchangeUnited StatesAZPhoenix85034http://www.avnet.comMid CapUS053807103853807103BBG000G99V31BBG000G99TC6BBG001S5NZJ2
WB6B.FTinkerine Studios Ltd.Tinkerine Studios Ltd. designs, manufactures, ...EURInformation TechnologyTechnology Hardware & EquipmentTechnology Hardware, Storage & PeripheralsFRAFrankfurt Stock ExchangeCanadaBCDeltaV4G 0A4http://www.tinkerine.comNano CapNaNNaNNaNNaNNaN
ZT1A.FZebra Technologies CorporationZebra Technologies Corporation, together with ...EURInformation TechnologyTechnology Hardware & EquipmentCommunications EquipmentFRAFrankfurt Stock ExchangeUnited StatesILLincolnshire60069http://www.zebra.comLarge CapUS9892071054989207105BBG000GD38T1BBG000GD2741BBG001S6SX73
ZU1.FSuzuken Co., Ltd.Suzuken Co., Ltd., together with its subsidiar...EURHealth CareHealth Care Equipment & ServicesHealth Care Providers & ServicesFRAFrankfurt Stock ExchangeJapanNaNNagoya461-8701http://www.suzuken.co.jpMid CapNaNNaNNaNNaNNaN
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64 rows × 19 columns

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" ], "text/plain": [ " name \\\n", "symbol \n", "109.F Castlight Health, Inc. \n", "1KT.F Keysight Technologies, Inc. \n", "1N1.F Nanalysis Scientific Corp. \n", "1YO.F Yangtze Optical Fibre And Cable Joint Stock Li... \n", "1ZU.F The Pennant Group, Inc. \n", "... ... \n", "V00.F Vocera Communications, Inc. \n", "VNI.F Avnet, Inc. \n", "WB6B.F Tinkerine Studios Ltd. \n", "ZT1A.F Zebra Technologies Corporation \n", "ZU1.F Suzuken Co., Ltd. \n", "\n", " summary currency \\\n", "symbol \n", "109.F Castlight Health, Inc. provides health navigat... EUR \n", "1KT.F Keysight Technologies, Inc. provides electroni... EUR \n", "1N1.F Nanalysis Scientific Corp., develops, manufact... EUR \n", "1YO.F Yangtze Optical Fibre And Cable Joint Stock Li... EUR \n", "1ZU.F The Pennant Group, Inc. provides healthcare se... EUR \n", "... ... ... \n", "V00.F Vocera Communications, Inc. provides secure, i... EUR \n", "VNI.F Avnet, Inc., a technology solutions company, m... EUR \n", "WB6B.F Tinkerine Studios Ltd. designs, manufactures, ... EUR \n", "ZT1A.F Zebra Technologies Corporation, together with ... EUR \n", "ZU1.F Suzuken Co., Ltd., together with its subsidiar... EUR \n", "\n", " sector industry_group \\\n", "symbol \n", "109.F Health Care Health Care Equipment & Services \n", "1KT.F Information Technology Technology Hardware & Equipment \n", "1N1.F Information Technology Technology Hardware & Equipment \n", "1YO.F Information Technology Technology Hardware & Equipment \n", "1ZU.F Health Care Health Care Equipment & Services \n", "... ... ... \n", "V00.F Information Technology Technology Hardware & Equipment \n", "VNI.F Information Technology Technology Hardware & Equipment \n", "WB6B.F Information Technology Technology Hardware & Equipment \n", "ZT1A.F Information Technology Technology Hardware & Equipment \n", "ZU1.F Health Care Health Care Equipment & Services \n", "\n", " industry exchange \\\n", "symbol \n", "109.F Health Care Providers & Services FRA \n", "1KT.F Electronic Equipment, Instruments & Components FRA \n", "1N1.F Electronic Equipment, Instruments & Components FRA \n", "1YO.F Communications Equipment FRA \n", "1ZU.F Health Care Equipment & Supplies FRA \n", "... ... ... \n", "V00.F Communications Equipment FRA \n", "VNI.F Electronic Equipment, Instruments & Components FRA \n", "WB6B.F Technology Hardware, Storage & Peripherals FRA \n", "ZT1A.F Communications Equipment FRA \n", "ZU1.F Health Care Providers & Services FRA \n", "\n", " market country state city \\\n", "symbol \n", "109.F Frankfurt Stock Exchange United States CA San Francisco \n", "1KT.F Frankfurt Stock Exchange United States CA Santa Rosa \n", "1N1.F Frankfurt Stock Exchange Canada AB Calgary \n", "1YO.F Frankfurt Stock Exchange China NaN Wuhan \n", "1ZU.F Frankfurt Stock Exchange United States ID Eagle \n", "... ... ... ... ... \n", "V00.F Frankfurt Stock Exchange United States CA San Jose \n", "VNI.F Frankfurt Stock Exchange United States AZ Phoenix \n", "WB6B.F Frankfurt Stock Exchange Canada BC Delta \n", "ZT1A.F Frankfurt Stock Exchange United States IL Lincolnshire \n", "ZU1.F Frankfurt Stock Exchange Japan NaN Nagoya \n", "\n", " zipcode website market_cap isin \\\n", "symbol \n", "109.F 94105 http://www.castlighthealth.com Small Cap NaN \n", "1KT.F 95403-1738 http://www.keysight.com Large Cap US49338L1035 \n", "1N1.F T2E 7C3 http://www.nanalysis.com Nano Cap NaN \n", "1YO.F 430073 http://www.yofc.com Small Cap NaN \n", "1ZU.F 83616 http://pennantgroup.com Small Cap US70805E1091 \n", "... ... ... ... ... \n", "V00.F 95126 http://www.vocera.com Small Cap NaN \n", "VNI.F 85034 http://www.avnet.com Mid Cap US0538071038 \n", "WB6B.F V4G 0A4 http://www.tinkerine.com Nano Cap NaN \n", "ZT1A.F 60069 http://www.zebra.com Large Cap US9892071054 \n", "ZU1.F 461-8701 http://www.suzuken.co.jp Mid Cap NaN \n", "\n", " cusip figi composite_figi shareclass_figi \n", "symbol \n", "109.F NaN NaN NaN NaN \n", "1KT.F 49338L103 BBG007DJZFD2 BBG007DJZFC3 BBG0059FN820 \n", "1N1.F NaN NaN NaN NaN \n", "1YO.F NaN NaN NaN NaN \n", "1ZU.F 7.08E+113 BBG00QJ35K78 BBG00QJ35K69 BBG00P33SZ15 \n", "... ... ... ... ... \n", "V00.F NaN NaN NaN NaN \n", "VNI.F 53807103 BBG000G99V31 BBG000G99TC6 BBG001S5NZJ2 \n", "WB6B.F NaN NaN NaN NaN \n", "ZT1A.F 989207105 BBG000GD38T1 BBG000GD2741 BBG001S6SX73 \n", "ZU1.F NaN NaN NaN NaN \n", "\n", "[64 rows x 19 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "equities.search(\n", " summary=[\"Robotics\", \"Education\"],\n", " industry_group=\"Equipment\",\n", " market=\"Frankfurt\",\n", " index=\".F\"\n", ")" ] }, { "cell_type": "markdown", "id": "7823c390", "metadata": {}, "source": [ "Lastly, the Finance Database has a direct integration with the [Finance Toolkit](https://github.com/JerBouma/FinanceToolkit) making it possible to do financial analysis on the companies you've found in the Finance Database. Returning to the earlier example of the 3 insurance companies in the Netherlands, it becomes possible to load these into the Finance Toolkit with the `to_toolkit` functionality. \n", "\n", "To be able to get started, you need to obtain an API Key from FinancialModelingPrep. This is used to gain access to 30+ years of financial statement both annually and quarterly. Note that the Free plan is limited to 250 requests each day, 5 years of data and only features companies listed on US exchanges.\n", "\n", "___ \n", "\n", "
Obtain an API Key from FinancialModelingPrep here.
\n", "___\n" ] }, { "cell_type": "code", "execution_count": 11, "id": "73a55437", "metadata": {}, "outputs": [], "source": [ "dutch_insurance_companies = equities.select(\n", " country=\"Netherlands\",\n", " industry=\"Insurance\",\n", " market=\"Euronext Amsterdam\",\n", ")\n", "\n", "toolkit = dutch_insurance_companies.to_toolkit(\n", " start_date=\"2010-01-01\",\n", " api_key=API_KEY\n", ")" ] }, { "cell_type": "markdown", "id": "50ef354a", "metadata": {}, "source": [ "With this integration, I can now access some of the most important financial metrics for these companies. Let's start simple with historical data." ] }, { "cell_type": "code", "execution_count": 12, "id": "858b90a4", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining historical data: 100%|██████████| 4/4 [00:00<00:00, 9.47it/s]\n" ] }, { "data": { "text/html": [ "
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OpenHighLow...Excess ReturnExcess VolatilityCumulative Return
AGN.ASASRNL.ASNN.ASBenchmarkAGN.ASASRNL.ASNN.ASBenchmarkAGN.ASASRNL.AS...NN.ASBenchmarkAGN.ASASRNL.ASNN.ASBenchmarkAGN.ASASRNL.ASNN.ASBenchmark
date
2010-01-044.58NaNNaN112.374.81NaNNaN113.394.56NaN...NaN-0.02150.0243NaNNaN0.01471.0NaNNaN1.0
2010-01-054.84NaNNaN113.264.88NaNNaN113.684.76NaN...NaN-0.03490.0243NaNNaN0.01471.0NaNNaN1.0027
2010-01-064.81NaNNaN113.524.85NaNNaN113.994.75NaN...NaN-0.03740.0243NaNNaN0.01470.9959NaNNaN1.0034
2010-01-074.76NaNNaN113.54.88NaNNaN114.334.7NaN...NaN-0.0340.0243NaNNaN0.01471.0163NaNNaN1.0076
2010-01-084.93NaNNaN113.895.09NaNNaN114.624.93NaN...NaN-0.03470.0243NaNNaN0.01471.0488NaNNaN1.011
..................................................................
2025-06-306.2356.3856.66617.386.2356.5456.66619.226.1156.06...-0.0395-0.03750.02430.02080.01980.01472.54.70234.98857.2255
2025-07-016.1756.7856.78616.366.2156.856.78618.836.1456.16...-0.0482-0.04280.02430.02080.01980.01472.50414.69064.96027.2231
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" ], "text/plain": [ " Open High \\\n", " AGN.AS ASRNL.AS NN.AS Benchmark AGN.AS ASRNL.AS NN.AS Benchmark \n", "date \n", "2010-01-04 4.58 NaN NaN 112.37 4.81 NaN NaN 113.39 \n", "2010-01-05 4.84 NaN NaN 113.26 4.88 NaN NaN 113.68 \n", "2010-01-06 4.81 NaN NaN 113.52 4.85 NaN NaN 113.99 \n", "2010-01-07 4.76 NaN NaN 113.5 4.88 NaN NaN 114.33 \n", "2010-01-08 4.93 NaN NaN 113.89 5.09 NaN NaN 114.62 \n", "... ... ... ... ... ... ... ... ... \n", "2025-06-30 6.23 56.38 56.66 617.38 6.23 56.54 56.66 619.22 \n", "2025-07-01 6.17 56.78 56.78 616.36 6.21 56.8 56.78 618.83 \n", "2025-07-02 6.19 55.94 56.8 617.24 6.21 56.32 56.82 620.49 \n", "2025-07-03 6.12 55.8 55.84 622.45 6.21 56.02 56.46 626.28 \n", "2025-07-04 6.17 55.82 56.26 NaN 6.21 55.94 56.36 NaN \n", "\n", " Low ... Excess Return Excess Volatility \\\n", " AGN.AS ASRNL.AS ... NN.AS Benchmark AGN.AS \n", "date ... \n", "2010-01-04 4.56 NaN ... NaN -0.0215 0.0243 \n", "2010-01-05 4.76 NaN ... NaN -0.0349 0.0243 \n", "2010-01-06 4.75 NaN ... NaN -0.0374 0.0243 \n", "2010-01-07 4.7 NaN ... NaN -0.034 0.0243 \n", "2010-01-08 4.93 NaN ... NaN -0.0347 0.0243 \n", "... ... ... ... ... ... ... \n", "2025-06-30 6.11 56.06 ... -0.0395 -0.0375 0.0243 \n", "2025-07-01 6.14 56.16 ... -0.0482 -0.0428 0.0243 \n", "2025-07-02 6.08 55.5 ... -0.0479 -0.0384 0.0243 \n", "2025-07-03 6.12 55.66 ... -0.0345 -0.0356 0.0243 \n", "2025-07-04 6.05 55.58 ... NaN NaN 0.0243 \n", "\n", " Cumulative Return \\\n", " ASRNL.AS NN.AS Benchmark AGN.AS ASRNL.AS NN.AS \n", "date \n", "2010-01-04 NaN NaN 0.0147 1.0 NaN NaN \n", "2010-01-05 NaN NaN 0.0147 1.0 NaN NaN \n", "2010-01-06 NaN NaN 0.0147 0.9959 NaN NaN \n", "2010-01-07 NaN NaN 0.0147 1.0163 NaN NaN \n", "2010-01-08 NaN NaN 0.0147 1.0488 NaN NaN \n", "... ... ... ... ... ... ... \n", "2025-06-30 0.0208 0.0198 0.0147 2.5 4.7023 4.9885 \n", "2025-07-01 0.0208 0.0198 0.0147 2.5041 4.6906 4.9602 \n", "2025-07-02 0.0208 0.0198 0.0147 2.4837 4.6439 4.9355 \n", "2025-07-03 0.0208 0.0198 0.0147 2.5244 4.6722 4.9797 \n", "2025-07-04 0.0208 0.0198 NaN 2.4634 4.6539 4.9443 \n", "\n", " \n", " Benchmark \n", "date \n", "2010-01-04 1.0 \n", "2010-01-05 1.0027 \n", "2010-01-06 1.0034 \n", "2010-01-07 1.0076 \n", "2010-01-08 1.011 \n", "... ... \n", "2025-06-30 7.2255 \n", "2025-07-01 7.2231 \n", "2025-07-02 7.2559 \n", "2025-07-03 7.3131 \n", "2025-07-04 NaN \n", "\n", "[4007 rows x 48 columns]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "toolkit.get_historical_data()" ] }, { "cell_type": "markdown", "id": "d0f4dbbb", "metadata": {}, "source": [ "And now let's make it more advanced by automatically calculating 60+ financial ratios for each. **This is just a small snippet of what is available within the Finance Toolkit, see for more information the GitHub page of the Finance Toolkit [here](https://github.com/JerBouma/FinanceToolkit) or the example Notebook [here](https://www.jeroenbouma.com/projects/financetoolkit/getting-started).**" ] }, { "cell_type": "code", "execution_count": 13, "id": "cefdf880", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining financial statements: 100%|██████████| 3/3 [00:03<00:00, 1.27s/it]\n" ] }, { "data": { "text/html": [ "
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AGN.ASDays of Inventory OutstandingNaNNaN0.00.00.0-14935.7305-12621.958-2182.1207-inf-inf-inf-inf-inf-2949.2888NaN
Days of Sales OutstandingNaN72.607343.666743.828244.154361.299650.495257.1464176.968937.833855.496849.238445.746370.568669.1609
Operating CycleNaNNaN43.666743.828244.1543-14874.4309-12571.4629-2124.9743-inf-inf-inf-inf-inf-2878.7201NaN
Days of Accounts Payable OutstandingNaNinf378.0598481.857358.0987428.0581362.581487.573infinfinfinfinf89.0992inf
Cash Conversion CycleNaNNaN-334.3931-438.0288-313.9444-15302.489-12934.0439-2612.5472-inf-inf-inf-inf-inf-2967.8194NaN
...................................................
NN.ASEV-to-EBITNaN1.82584.65820.72074.68883.62593.91753.86244.39044.82792.8893.84867.93175.91724.9614
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201 rows × 15 columns

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" ], "text/plain": [ " 2010 2011 \\\n", "AGN.AS Days of Inventory Outstanding NaN NaN \n", " Days of Sales Outstanding NaN 72.6073 \n", " Operating Cycle NaN NaN \n", " Days of Accounts Payable Outstanding NaN inf \n", " Cash Conversion Cycle NaN NaN \n", "... ... ... \n", "NN.AS EV-to-EBIT NaN 1.8258 \n", " EV-to-EBITDA NaN 1.6644 \n", " EV-to-Operating-Cash-Flow NaN 1.7384 \n", " Tangible Asset Value NaN 22688000000.0 \n", " Net Current Asset Value NaN 18958000000.0 \n", "\n", " 2012 2013 \\\n", "AGN.AS Days of Inventory Outstanding 0.0 0.0 \n", " Days of Sales Outstanding 43.6667 43.8282 \n", " Operating Cycle 43.6667 43.8282 \n", " Days of Accounts Payable Outstanding 378.0598 481.857 \n", " Cash Conversion Cycle -334.3931 -438.0288 \n", "... ... ... \n", "NN.AS EV-to-EBIT 4.6582 0.7207 \n", " EV-to-EBITDA 4.1899 6.7609 \n", " EV-to-Operating-Cash-Flow 9.8575 -0.0754 \n", " Tangible Asset Value 25889000000.0 14031000000.0 \n", " Net Current Asset Value 123696000000.0 8941000000.0 \n", "\n", " 2014 2015 \\\n", "AGN.AS Days of Inventory Outstanding 0.0 -14935.7305 \n", " Days of Sales Outstanding 44.1543 61.2996 \n", " Operating Cycle 44.1543 -14874.4309 \n", " Days of Accounts Payable Outstanding 358.0987 428.0581 \n", " Cash Conversion Cycle -313.9444 -15302.489 \n", "... ... ... \n", "NN.AS EV-to-EBIT 4.6888 3.6259 \n", " EV-to-EBITDA 4.2803 3.5016 \n", " EV-to-Operating-Cash-Flow -1.2079 -1.2314 \n", " Tangible Asset Value 21152000000.0 21204000000.0 \n", " Net Current Asset Value 9762000000.0 10012000000.0 \n", "\n", " 2016 2017 \\\n", "AGN.AS Days of Inventory Outstanding -12621.958 -2182.1207 \n", " Days of Sales Outstanding 50.4952 57.1464 \n", " Operating Cycle -12571.4629 -2124.9743 \n", " Days of Accounts Payable Outstanding 362.581 487.573 \n", " Cash Conversion Cycle -12934.0439 -2612.5472 \n", "... ... ... \n", "NN.AS EV-to-EBIT 3.9175 3.8624 \n", " EV-to-EBITDA 3.8356 3.5928 \n", " EV-to-Operating-Cash-Flow -3.7887 -2.0216 \n", " Tangible Asset Value 23451000000.0 23407000000.0 \n", " Net Current Asset Value 12127000000.0 1577000000.0 \n", "\n", " 2018 2019 \\\n", "AGN.AS Days of Inventory Outstanding -inf -inf \n", " Days of Sales Outstanding 176.9689 37.8338 \n", " Operating Cycle -inf -inf \n", " Days of Accounts Payable Outstanding inf inf \n", " Cash Conversion Cycle -inf -inf \n", "... ... ... \n", "NN.AS EV-to-EBIT 4.3904 4.8279 \n", " EV-to-EBITDA 3.9097 5.4029 \n", " EV-to-Operating-Cash-Flow -3.6272 5.0242 \n", " Tangible Asset Value 24316000000.0 32253000000.0 \n", " Net Current Asset Value 112317000000.0 123028000000.0 \n", "\n", " 2020 2021 \\\n", "AGN.AS Days of Inventory Outstanding -inf -inf \n", " Days of Sales Outstanding 55.4968 49.2384 \n", " Operating Cycle -inf -inf \n", " Days of Accounts Payable Outstanding inf inf \n", " Cash Conversion Cycle -inf -inf \n", "... ... ... \n", "NN.AS EV-to-EBIT 2.889 3.8486 \n", " EV-to-EBITDA 2.7514 4.9543 \n", " EV-to-Operating-Cash-Flow 1.1463 -6.5414 \n", " Tangible Asset Value 38239000000.0 34369000000.0 \n", " Net Current Asset Value 129555000000.0 114010000000.0 \n", "\n", " 2022 2023 \\\n", "AGN.AS Days of Inventory Outstanding -inf -2949.2888 \n", " Days of Sales Outstanding 45.7463 70.5686 \n", " Operating Cycle -inf -2878.7201 \n", " Days of Accounts Payable Outstanding inf 89.0992 \n", " Cash Conversion Cycle -inf -2967.8194 \n", "... ... ... \n", "NN.AS EV-to-EBIT 7.9317 5.9172 \n", " EV-to-EBITDA 7.4963 2.0107 \n", " EV-to-Operating-Cash-Flow -2.2035 238.7875 \n", " Tangible Asset Value 16961000000.0 20227000000.0 \n", " Net Current Asset Value 87733000000.0 105289000000.0 \n", "\n", " 2024 \n", "AGN.AS Days of Inventory Outstanding NaN \n", " Days of Sales Outstanding 69.1609 \n", " Operating Cycle NaN \n", " Days of Accounts Payable Outstanding inf \n", " Cash Conversion Cycle NaN \n", "... ... \n", "NN.AS EV-to-EBIT 4.9614 \n", " EV-to-EBITDA 1.557 \n", " EV-to-Operating-Cash-Flow -39.097 \n", " Tangible Asset Value 20783000000.0 \n", " Net Current Asset Value 112978000000.0 \n", "\n", "[201 rows x 15 columns]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "toolkit.ratios.collect_all_ratios()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "754b1ee6", "metadata": {}, "source": [ "All of these methods are also available for the other asset classes. The only difference is that the class name changes and the available columns. For example, for ETFs you would use `fd.ETFs()` instead of `fd.Equities()` and the `select` option has parameters such as `category_group` and `family` instead." ] }, { "cell_type": "code", "execution_count": 14, "id": "f0e17359", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namecurrencysummarycategory_groupcategoryfamilyexchange
symbol
^ADFI-IVNFIELD DYNAMIC FIXED INCOME ETFUSDThe NFIELD DYNAMIC FIXED INCOME ETF (ADFI) is ...Fixed IncomeCorporate BondsNaNASE
^BNDVANGUARD BD IDX FDUSDThe Vanguard Total Bond Market ETF seeks to tr...Fixed IncomeInvestment Grade BondsVanguard Asset ManagementNIM
^BNDXVANGUARD CHARLOTTEUSDThe Vanguard Total International Bond ETF seek...Fixed IncomeInvestment Grade BondsVanguard Asset ManagementNIM
^VCITVANGUARD SCOTTSDALUSDThe Vanguard Intermediate-Term Corporate Bond ...Fixed IncomeCorporate BondsVanguard Asset ManagementNIM
^VCLTVANGUARD SCOTTSDALUSDThe Vanguard Long-Term Corporate Bond ETF seek...Fixed IncomeCorporate BondsVanguard Asset ManagementNIM
........................
ZUS-U.TOBMO Ultra Short-Term US Bond ETF (US Dollar Un...USDBMO Ultra Short-Term US Bond ETF seeks to prov...Fixed IncomeCorporate BondsBMO Capital MarketsTOR
ZUS-V.TOBMO Ultra Short-Term US Bond ETF (US Dollar Ac...USDBMO Ultra Short-Term US Bond ETF seeks to prov...Fixed IncomeCorporate BondsBMO Capital MarketsTOR
0A12.LInvesco Ultra Short Duration ETFNaNThe investment seeks maximum current income, c...Fixed IncomeCorporate BondsInvesco Investment ManagementNaN
EMAG.SNVanEck Vectors Emerging Markets Aggregate Bond...NaNThe investment seeks to replicate as closely a...Fixed IncomeCorporate BondsVanEck Asset ManagementNaN
EMLC.SNVanEck Vectors J.P. Morgan EM Local Currency B...NaNThe investment seeks to replicate as closely a...Fixed IncomeCorporate BondsVanEck Asset ManagementNaN
\n", "

6691 rows × 7 columns

\n", "
" ], "text/plain": [ " name currency \\\n", "symbol \n", "^ADFI-IV NFIELD DYNAMIC FIXED INCOME ETF USD \n", "^BND VANGUARD BD IDX FD USD \n", "^BNDX VANGUARD CHARLOTTE USD \n", "^VCIT VANGUARD SCOTTSDAL USD \n", "^VCLT VANGUARD SCOTTSDAL USD \n", "... ... ... \n", "ZUS-U.TO BMO Ultra Short-Term US Bond ETF (US Dollar Un... USD \n", "ZUS-V.TO BMO Ultra Short-Term US Bond ETF (US Dollar Ac... USD \n", "0A12.L Invesco Ultra Short Duration ETF NaN \n", "EMAG.SN VanEck Vectors Emerging Markets Aggregate Bond... NaN \n", "EMLC.SN VanEck Vectors J.P. Morgan EM Local Currency B... NaN \n", "\n", " summary category_group \\\n", "symbol \n", "^ADFI-IV The NFIELD DYNAMIC FIXED INCOME ETF (ADFI) is ... Fixed Income \n", "^BND The Vanguard Total Bond Market ETF seeks to tr... Fixed Income \n", "^BNDX The Vanguard Total International Bond ETF seek... Fixed Income \n", "^VCIT The Vanguard Intermediate-Term Corporate Bond ... Fixed Income \n", "^VCLT The Vanguard Long-Term Corporate Bond ETF seek... Fixed Income \n", "... ... ... \n", "ZUS-U.TO BMO Ultra Short-Term US Bond ETF seeks to prov... Fixed Income \n", "ZUS-V.TO BMO Ultra Short-Term US Bond ETF seeks to prov... Fixed Income \n", "0A12.L The investment seeks maximum current income, c... Fixed Income \n", "EMAG.SN The investment seeks to replicate as closely a... Fixed Income \n", "EMLC.SN The investment seeks to replicate as closely a... Fixed Income \n", "\n", " category family exchange \n", "symbol \n", "^ADFI-IV Corporate Bonds NaN ASE \n", "^BND Investment Grade Bonds Vanguard Asset Management NIM \n", "^BNDX Investment Grade Bonds Vanguard Asset Management NIM \n", "^VCIT Corporate Bonds Vanguard Asset Management NIM \n", "^VCLT Corporate Bonds Vanguard Asset Management NIM \n", "... ... ... ... \n", "ZUS-U.TO Corporate Bonds BMO Capital Markets TOR \n", "ZUS-V.TO Corporate Bonds BMO Capital Markets TOR \n", "0A12.L Corporate Bonds Invesco Investment Management NaN \n", "EMAG.SN Corporate Bonds VanEck Asset Management NaN \n", "EMLC.SN Corporate Bonds VanEck Asset Management NaN \n", "\n", "[6691 rows x 7 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Obtain all sectors from the database\n", "etfs = fd.ETFs()\n", "\n", "etfs.select(\n", " category_group=\"Fixed Income\"\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "0ab89b95", "metadata": {}, "source": [ "This also translates to the available options, for example let's select `fd.Indices()` instead." ] }, { "cell_type": "code", "execution_count": 15, "id": "e21194f5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'category_group': array(['Alternatives', 'Cash', 'Commodities', 'Communication Services',\n", " 'Consumer Discretionary', 'Consumer Staples', 'Currencies',\n", " 'Derivatives', 'Energy', 'Equities', 'Financials', 'Fixed Income',\n", " 'Health Care', 'Industrials', 'Information Technology',\n", " 'Materials', 'Real Estate', 'Utilities'], dtype=object),\n", " 'category': array(['Alternative', 'Blend', 'Bonds', 'Cash', 'Commercial Real Estate',\n", " 'Commodities Broad Basket', 'Communications',\n", " 'Consumer Discretionary', 'Consumer Staples', 'Corporate Bonds',\n", " 'Currencies', 'Derivatives', 'Developed Markets',\n", " 'Emerging Markets', 'Energy', 'Equities', 'Factors', 'Financials',\n", " 'Frontier Markets', 'Government Bonds', 'Growth', 'Health Care',\n", " 'High Yield Bonds', 'Industrials',\n", " 'Inflation-Protected Securities', 'Investment Grade Bonds',\n", " 'Large Cap', 'Materials', 'Micro Cap', 'Mid Cap',\n", " 'Money Market Instruments', 'Municipal Bonds', 'REITs',\n", " 'Real Estate Development', 'Real Estate Services',\n", " 'Residential Real Estate', 'Small Cap', 'Technology', 'Trading',\n", " 'Treasury Bonds', 'Utilities', 'Value'], dtype=object),\n", " 'currency': array(['AED', 'AUD', 'BGN', 'BRL', 'CAD', 'CHF', 'CLP', 'CNY', 'COP',\n", " 'CZK', 'DKK', 'EGP', 'EUR', 'GBP', 'GBp', 'HKD', 'HUF', 'IDR',\n", " 'ILS', 'INR', 'ISK', 'JPY', 'KEW', 'KRW', 'KWD', 'LKR', 'MCE',\n", " 'MXN', 'MYR', 'NOK', 'NZD', 'PEN', 'PHP', 'PKR', 'PLN', 'QAR',\n", " 'RUB', 'SAR', 'SEK', 'SGD', 'THB', 'TRY', 'TWD', 'USD', 'ZAR'],\n", " dtype=object),\n", " 'exchange': array(['AMS', 'ASE', 'ASX', 'ATH', 'BRU', 'BSE', 'BUD', 'BUE', 'CAI',\n", " 'CCS', 'CSE', 'DJI', 'DOH', 'EBS', 'ENX', 'FGI', 'FSI', 'GER',\n", " 'HKG', 'ISE', 'IST', 'JKT', 'JNB', 'KLS', 'KOE', 'KSC', 'LIS',\n", " 'LIT', 'MCE', 'MCX', 'MEX', 'MIL', 'NIM', 'NSI', 'NYB', 'NYS',\n", " 'NZE', 'OPI', 'OSA', 'OSL', 'PAR', 'PHS', 'PRA', 'RIS', 'SAO',\n", " 'SAU', 'SES', 'SET', 'SGO', 'SHH', 'SHZ', 'SNP', 'STO', 'STU',\n", " 'TAI', 'TAL', 'TLV', 'TSI', 'TWO', 'VAN', 'VIE', 'WCB', 'ZRH'],\n", " dtype=object)}" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "indices = fd.Indices()\n", "\n", "indices.show_options()" ] }, { "cell_type": "markdown", "id": "0c86e3cb", "metadata": {}, "source": [ "And lastly, both the `search` and `to_toolkit` metrics also apply to each of the asset classes, using `fd.Funds()` and `fd.Cryptos()` respectively." ] }, { "cell_type": "code", "execution_count": 16, "id": "072d64d8", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namecurrencysummarycategory_groupcategoryfamilyexchange
symbol
0P000015HA.FCasermed Protecci&#195;&#179;n 6 PPEURCasermed Protección 6 PP is a pension plan off...FinancialsAllocationSa Nostra Seguros de Vida SAFRA
0P000015V5.FBK Revalorizaci&#195;&#179;n Europa 2022 PPEURBK Revalorización Europa 2022 PP is a pension ...FinancialsBondsBankinterFRA
0P000015VC.FBankia Protegido Renta 2023 PPEURBankia Protegido Renta 2023 PP is a protected ...FinancialsBondsBankia FondosFRA
0P000017AE.FSantander Universidades RF Mixta PPEURSantander Universidades RF Mixta PP is a mixed...Fixed IncomeBondsSantander Asset Management SGIICFRA
0P000017AF.FOpenBank Monetario PPEUROpenBank Monetario PP is a monetary or money m...CashMoney Market InstrumentsSantander Asset Management SGIICFRA
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XXINTECB2P08.MXMultifondo De Prevision 5 Banorte Generali Sie...MXNMultifondo De Prevision 5 Banorte Generali Sie...FinancialsPension PlansNaNMEX
XXINTECB2P09.MXMultifondo De Prevision 5 Banorte Generali Sie...MXNMultifondo De Prevision 5 Banorte Generali Sie...FinancialsPension PlansNaNMEX
XXINTECB2P10.MXMultifondo De Prevision 5 Banorte Generali Sie...MXNMultifondo De Prevision 5 Banorte Generali Sie...FinancialsPension PlansNaNMEX
XXINTECB2V1.MXMultifondo De Prevision 5 Banorte Generali Sie...MXNMultifondo De Prevision 5 Banorte Generali Sie...FinancialsPension PlansNaNMEX
XXINTECB2V2.MXMultifondo De Prevision 5 Banorte Generali Sie...MXNMultifondo De Prevision 5 Banorte Generali Sie...FinancialsPension PlansNaNMEX
\n", "

625 rows × 7 columns

\n", "
" ], "text/plain": [ " name currency \\\n", "symbol \n", "0P000015HA.F Casermed Protección 6 PP EUR \n", "0P000015V5.F BK Revalorización Europa 2022 PP EUR \n", "0P000015VC.F Bankia Protegido Renta 2023 PP EUR \n", "0P000017AE.F Santander Universidades RF Mixta PP EUR \n", "0P000017AF.F OpenBank Monetario PP EUR \n", "... ... ... \n", "XXINTECB2P08.MX Multifondo De Prevision 5 Banorte Generali Sie... MXN \n", "XXINTECB2P09.MX Multifondo De Prevision 5 Banorte Generali Sie... MXN \n", "XXINTECB2P10.MX Multifondo De Prevision 5 Banorte Generali Sie... MXN \n", "XXINTECB2V1.MX Multifondo De Prevision 5 Banorte Generali Sie... MXN \n", "XXINTECB2V2.MX Multifondo De Prevision 5 Banorte Generali Sie... MXN \n", "\n", " summary \\\n", "symbol \n", "0P000015HA.F Casermed Protección 6 PP is a pension plan off... \n", "0P000015V5.F BK Revalorización Europa 2022 PP is a pension ... \n", "0P000015VC.F Bankia Protegido Renta 2023 PP is a protected ... \n", "0P000017AE.F Santander Universidades RF Mixta PP is a mixed... \n", "0P000017AF.F OpenBank Monetario PP is a monetary or money m... \n", "... ... \n", "XXINTECB2P08.MX Multifondo De Prevision 5 Banorte Generali Sie... \n", "XXINTECB2P09.MX Multifondo De Prevision 5 Banorte Generali Sie... \n", "XXINTECB2P10.MX Multifondo De Prevision 5 Banorte Generali Sie... \n", "XXINTECB2V1.MX Multifondo De Prevision 5 Banorte Generali Sie... \n", "XXINTECB2V2.MX Multifondo De Prevision 5 Banorte Generali Sie... \n", "\n", " category_group category \\\n", "symbol \n", "0P000015HA.F Financials Allocation \n", "0P000015V5.F Financials Bonds \n", "0P000015VC.F Financials Bonds \n", "0P000017AE.F Fixed Income Bonds \n", "0P000017AF.F Cash Money Market Instruments \n", "... ... ... \n", "XXINTECB2P08.MX Financials Pension Plans \n", "XXINTECB2P09.MX Financials Pension Plans \n", "XXINTECB2P10.MX Financials Pension Plans \n", "XXINTECB2V1.MX Financials Pension Plans \n", "XXINTECB2V2.MX Financials Pension Plans \n", "\n", " family exchange \n", "symbol \n", "0P000015HA.F Sa Nostra Seguros de Vida SA FRA \n", "0P000015V5.F Bankinter FRA \n", "0P000015VC.F Bankia Fondos FRA \n", "0P000017AE.F Santander Asset Management SGIIC FRA \n", "0P000017AF.F Santander Asset Management SGIIC FRA \n", "... ... ... \n", "XXINTECB2P08.MX NaN MEX \n", "XXINTECB2P09.MX NaN MEX \n", "XXINTECB2P10.MX NaN MEX \n", "XXINTECB2V1.MX NaN MEX \n", "XXINTECB2V2.MX NaN MEX \n", "\n", "[625 rows x 7 columns]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "funds = fd.Funds()\n", "\n", "funds.search(summary=\"Pension\")" ] }, { "cell_type": "code", "execution_count": 17, "id": "d1a556c1", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining historical data: 100%|██████████| 6/6 [00:00<00:00, 9.45it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2025-07-05 08:25:50 - financetoolkit - INFO - The following tickers acquired historical data from FinancialModelingPrep: SPY, ETH-USD\n", "2025-07-05 08:25:50 - financetoolkit - INFO - The following tickers acquired historical data from YahooFinance: ETH-CAD, ETH-EUR, ETH-BTC, ETH-GBP\n" ] }, { "data": { "text/html": [ "
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OpenHigh...Excess VolatilityCumulative Return
ETH-BTCETH-CADETH-EURETH-GBPETH-USDBenchmarkETH-BTCETH-CADETH-EURETH-GBP...ETH-EURETH-GBPETH-USDBenchmarkETH-BTCETH-CADETH-EURETH-GBPETH-USDBenchmark
Date
2020Q10.0207188.3557120.4332107.4132132.3260.560.0208188.9573121.6618108.1101...0.54140.53860.5580.23811.01.01.01.01.01.0
2020Q20.0248311.344202.6958185.2006227.81303.990.025313.9839204.9717187.0433...0.3010.29550.33050.13781.19811.63331.66271.69671.69431.2016
2020Q30.0332481.9008306.6297279.8633359.93333.090.0335480.6405307.8944279.5126...0.28350.28320.30220.08151.61352.54682.53422.58792.70431.3102
2020Q40.0261958.4705611.1484551.5031752.87371.780.0258962.0697613.3465553.4235...0.30990.30640.31430.07261.22714.99324.98525.01155.54311.469
2021Q10.03132330.14531574.73111343.01991841.03395.340.03282446.77641660.73821413.1154...0.45010.45190.45990.06991.574912.814313.501512.922914.42741.5623
2021Q20.06032683.08721818.60831563.70042165.64427.210.06532830.39261925.11671650.7152...0.56380.56450.57320.05053.135314.987215.834415.274617.10791.6929
2021Q30.06863638.27342458.92582124.47172849.71436.020.06933856.90582630.74562260.3408...0.39470.38960.39840.05483.309220.241821.405920.696822.54631.7026
2021Q40.07874733.42383279.63842751.20613710.01475.640.07864845.94383359.88312816.7505...0.30130.29710.31610.06283.840624.747726.723725.273927.6211.8911
2022Q10.07194226.21243033.07032576.79763386.69457.890.07254297.57913093.51172616.022...0.34850.35220.35920.09833.483121.811424.460423.181924.671.8038
2022Q20.05471416.44171052.4261906.38261099.09376.240.05481423.00021057.0552910.3747...0.36740.36190.37120.13832.60397.30428.40698.15088.04091.5132
2022Q30.06821826.52861358.79991195.51711336.04361.80.06811877.89541394.63591225.6317...0.39510.39450.41410.11043.29959.764311.182211.03839.98611.4386
2022Q40.07221627.46451118.1682990.96051199.19381.57250.07251635.24511123.4692996.1058...0.29720.2860.32050.11053.49288.63359.20889.18678.98141.5457
2023Q10.06332433.05931653.95811456.78151793.68404.660.06272480.47271686.79161484.9393...0.2260.23210.23320.08383.091812.888613.569513.440913.69111.6628
2023Q20.06082422.7911674.59381446.02231851.98441.440.0612491.94781725.38531487.58...0.15560.15530.18920.05332.937213.048814.067313.637214.52941.8071
2023Q30.06122230.11181564.91151354.43511667.2429.98670.06212268.8451590.47681377.9132...0.14530.14630.14360.05522.995212.046713.011612.694412.55521.7486
2023Q40.05473050.6752080.77371805.79312291.51474.3250.05463079.8132100.33111822.6219...0.21230.21420.21860.06212.62816.162117.111916.707717.14061.9469
2024Q10.05024744.30373251.66092781.5433507.31523.6750.05084817.60213301.89822824.396...0.22990.23380.26140.05022.434825.194426.808625.801627.39312.1524
2024Q20.05594620.09963147.04882667.15843373.34546.140.05584658.49953173.20532689.3262...0.24220.24080.29880.05242.676324.556725.969324.763725.79182.2527
2024Q30.04063621.09112397.51292002.01832657.9570.420.04073628.95782402.04612006.9142...0.28790.28220.28480.07481.956519.100419.651818.454119.54672.379
2024Q40.03584824.43213211.50272662.97093355.44589.910.03654936.94583287.11432724.6816...0.2780.27050.28180.05951.748825.606926.622624.839725.02492.4383
2025Q10.02212627.94731680.20891411.54111807.51549.830.02222657.08351698.83741427.1909...0.31570.31580.30610.07691.05813.741213.773412.964313.69122.3342
2025Q20.02273336.11062079.34641776.19362500.7617.380.02333452.48052150.4471838.4309...0.39070.37780.32350.13971.115918.191917.602416.929718.68162.5858
2025Q30.02363493.29862178.93771883.46332508.4358622.450.02393579.70832239.40211930.1808...0.42740.45160.40390.02881.140118.699818.170117.60718.92642.6171
\n", "

23 rows × 72 columns

\n", "
" ], "text/plain": [ " Open High \\\n", " ETH-BTC ETH-CAD ETH-EUR ETH-GBP ETH-USD Benchmark ETH-BTC \n", "Date \n", "2020Q1 0.0207 188.3557 120.4332 107.4132 132.3 260.56 0.0208 \n", "2020Q2 0.0248 311.344 202.6958 185.2006 227.81 303.99 0.025 \n", "2020Q3 0.0332 481.9008 306.6297 279.8633 359.93 333.09 0.0335 \n", "2020Q4 0.0261 958.4705 611.1484 551.5031 752.87 371.78 0.0258 \n", "2021Q1 0.0313 2330.1453 1574.7311 1343.0199 1841.03 395.34 0.0328 \n", "2021Q2 0.0603 2683.0872 1818.6083 1563.7004 2165.64 427.21 0.0653 \n", "2021Q3 0.0686 3638.2734 2458.9258 2124.4717 2849.71 436.02 0.0693 \n", "2021Q4 0.0787 4733.4238 3279.6384 2751.2061 3710.01 475.64 0.0786 \n", "2022Q1 0.0719 4226.2124 3033.0703 2576.7976 3386.69 457.89 0.0725 \n", "2022Q2 0.0547 1416.4417 1052.4261 906.3826 1099.09 376.24 0.0548 \n", "2022Q3 0.0682 1826.5286 1358.7999 1195.5171 1336.04 361.8 0.0681 \n", "2022Q4 0.0722 1627.4645 1118.1682 990.9605 1199.19 381.5725 0.0725 \n", "2023Q1 0.0633 2433.0593 1653.9581 1456.7815 1793.68 404.66 0.0627 \n", "2023Q2 0.0608 2422.791 1674.5938 1446.0223 1851.98 441.44 0.061 \n", "2023Q3 0.0612 2230.1118 1564.9115 1354.4351 1667.2 429.9867 0.0621 \n", "2023Q4 0.0547 3050.675 2080.7737 1805.7931 2291.51 474.325 0.0546 \n", "2024Q1 0.0502 4744.3037 3251.6609 2781.543 3507.31 523.675 0.0508 \n", "2024Q2 0.0559 4620.0996 3147.0488 2667.1584 3373.34 546.14 0.0558 \n", "2024Q3 0.0406 3621.0911 2397.5129 2002.0183 2657.9 570.42 0.0407 \n", "2024Q4 0.0358 4824.4321 3211.5027 2662.9709 3355.44 589.91 0.0365 \n", "2025Q1 0.0221 2627.9473 1680.2089 1411.5411 1807.51 549.83 0.0222 \n", "2025Q2 0.0227 3336.1106 2079.3464 1776.1936 2500.7 617.38 0.0233 \n", "2025Q3 0.0236 3493.2986 2178.9377 1883.4633 2508.4358 622.45 0.0239 \n", "\n", " ... Excess Volatility \\\n", " ETH-CAD ETH-EUR ETH-GBP ... ETH-EUR ETH-GBP ETH-USD \n", "Date ... \n", "2020Q1 188.9573 121.6618 108.1101 ... 0.5414 0.5386 0.558 \n", "2020Q2 313.9839 204.9717 187.0433 ... 0.301 0.2955 0.3305 \n", "2020Q3 480.6405 307.8944 279.5126 ... 0.2835 0.2832 0.3022 \n", "2020Q4 962.0697 613.3465 553.4235 ... 0.3099 0.3064 0.3143 \n", "2021Q1 2446.7764 1660.7382 1413.1154 ... 0.4501 0.4519 0.4599 \n", "2021Q2 2830.3926 1925.1167 1650.7152 ... 0.5638 0.5645 0.5732 \n", "2021Q3 3856.9058 2630.7456 2260.3408 ... 0.3947 0.3896 0.3984 \n", "2021Q4 4845.9438 3359.8831 2816.7505 ... 0.3013 0.2971 0.3161 \n", "2022Q1 4297.5791 3093.5117 2616.022 ... 0.3485 0.3522 0.3592 \n", "2022Q2 1423.0002 1057.0552 910.3747 ... 0.3674 0.3619 0.3712 \n", "2022Q3 1877.8954 1394.6359 1225.6317 ... 0.3951 0.3945 0.4141 \n", "2022Q4 1635.2451 1123.4692 996.1058 ... 0.2972 0.286 0.3205 \n", "2023Q1 2480.4727 1686.7916 1484.9393 ... 0.226 0.2321 0.2332 \n", "2023Q2 2491.9478 1725.3853 1487.58 ... 0.1556 0.1553 0.1892 \n", "2023Q3 2268.845 1590.4768 1377.9132 ... 0.1453 0.1463 0.1436 \n", "2023Q4 3079.813 2100.3311 1822.6219 ... 0.2123 0.2142 0.2186 \n", "2024Q1 4817.6021 3301.8982 2824.396 ... 0.2299 0.2338 0.2614 \n", "2024Q2 4658.4995 3173.2053 2689.3262 ... 0.2422 0.2408 0.2988 \n", "2024Q3 3628.9578 2402.0461 2006.9142 ... 0.2879 0.2822 0.2848 \n", "2024Q4 4936.9458 3287.1143 2724.6816 ... 0.278 0.2705 0.2818 \n", "2025Q1 2657.0835 1698.8374 1427.1909 ... 0.3157 0.3158 0.3061 \n", "2025Q2 3452.4805 2150.447 1838.4309 ... 0.3907 0.3778 0.3235 \n", "2025Q3 3579.7083 2239.4021 1930.1808 ... 0.4274 0.4516 0.4039 \n", "\n", " Cumulative Return \n", " Benchmark ETH-BTC ETH-CAD ETH-EUR ETH-GBP ETH-USD Benchmark \n", "Date \n", "2020Q1 0.2381 1.0 1.0 1.0 1.0 1.0 1.0 \n", "2020Q2 0.1378 1.1981 1.6333 1.6627 1.6967 1.6943 1.2016 \n", "2020Q3 0.0815 1.6135 2.5468 2.5342 2.5879 2.7043 1.3102 \n", "2020Q4 0.0726 1.2271 4.9932 4.9852 5.0115 5.5431 1.469 \n", "2021Q1 0.0699 1.5749 12.8143 13.5015 12.9229 14.4274 1.5623 \n", "2021Q2 0.0505 3.1353 14.9872 15.8344 15.2746 17.1079 1.6929 \n", "2021Q3 0.0548 3.3092 20.2418 21.4059 20.6968 22.5463 1.7026 \n", "2021Q4 0.0628 3.8406 24.7477 26.7237 25.2739 27.621 1.8911 \n", "2022Q1 0.0983 3.4831 21.8114 24.4604 23.1819 24.67 1.8038 \n", "2022Q2 0.1383 2.6039 7.3042 8.4069 8.1508 8.0409 1.5132 \n", "2022Q3 0.1104 3.2995 9.7643 11.1822 11.0383 9.9861 1.4386 \n", "2022Q4 0.1105 3.4928 8.6335 9.2088 9.1867 8.9814 1.5457 \n", "2023Q1 0.0838 3.0918 12.8886 13.5695 13.4409 13.6911 1.6628 \n", "2023Q2 0.0533 2.9372 13.0488 14.0673 13.6372 14.5294 1.8071 \n", "2023Q3 0.0552 2.9952 12.0467 13.0116 12.6944 12.5552 1.7486 \n", "2023Q4 0.0621 2.628 16.1621 17.1119 16.7077 17.1406 1.9469 \n", "2024Q1 0.0502 2.4348 25.1944 26.8086 25.8016 27.3931 2.1524 \n", "2024Q2 0.0524 2.6763 24.5567 25.9693 24.7637 25.7918 2.2527 \n", "2024Q3 0.0748 1.9565 19.1004 19.6518 18.4541 19.5467 2.379 \n", "2024Q4 0.0595 1.7488 25.6069 26.6226 24.8397 25.0249 2.4383 \n", "2025Q1 0.0769 1.058 13.7412 13.7734 12.9643 13.6912 2.3342 \n", "2025Q2 0.1397 1.1159 18.1919 17.6024 16.9297 18.6816 2.5858 \n", "2025Q3 0.0288 1.1401 18.6998 18.1701 17.607 18.9264 2.6171 \n", "\n", "[23 rows x 72 columns]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cryptos = fd.Cryptos()\n", "\n", "eth_cryptos = cryptos.select(\n", " cryptocurrency=\"ETH\"\n", ")\n", "\n", "cryptos_toolkit = eth_cryptos.to_toolkit(\n", " api_key=API_KEY,\n", " start_date=\"2020-01-01\"\n", ")\n", "\n", "cryptos_toolkit.get_historical_data(period=\"quarterly\")" ] } ], "metadata": { "kernelspec": { "display_name": "financedatabase-Id8SGqlw-py3.12", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.1" } }, "nbformat": 4, "nbformat_minor": 5 }