Finance Domain Data Products
The US equity market datasets for public companies listed in NYSE or NASDAQ exchanges, collected directly from the Securities and Exchange Commission (SEC) filings
- US Equity Markets: Standardized Income Statements
Quarterly and annual consolidated income statements for publicly traded companies in the US equity marketsStarting From $449BECOME A SUBSCRIBER
- US Equity Markets: Standardized Balance Sheets
Quarterly and annual consolidated balance sheets for companies traded in the US equity marketsStarting From $499BECOME A SUBSCRIBER
- Valuation Ratios and Growth History
Year over year, 3-year and 5-year growth statistics and profit margins for publicly traded companies in the US equity marketsStarting From $595BECOME A SUBSCRIBER
- US Equity Markets: Standardized Statement of Cash Flows
Quarterly and annual statement of cash flows for companies traded in the US equity marketsStarting From $499BECOME A SUBSCRIBER
- US Equity Markets Training Data
A data snapshot of more than 3000 US public companies' financials, stats and calculations for data science training purposesFree to
UseBECOME A SUBSCRIBER
- Daily Cryptocurrencies' Prices and Key Indicators
Historical daily market prices and key statistics data for 3000+ cryptocurrencies since 2013Starting From $9.99BECOME A SUBSCRIBER
- Daily US Equity Market Company Benchmarking Data
Updated daily, US equity market benchmarking data with financial statements and technical price indicators for 3,000 US public companiesFor Pricing Contact UsBECOME A SUBSCRIBER
- Historical Daily USD and Most Tradable Currencies FX Rates since 1971
Historical daily exchange rates for 35 foreign currencies relative to the U.S. Dollar and most tradable currencies based on Federal Reserve data since 1971Free to
UseBECOME A SUBSCRIBER
Questions & Answers
What is Finance Data?
There is a vast amount of finance data that comes in all sorts of variety in the world. Organizations, exchanges, regulators, traders, arbitrators, market makers and sovereign governments all generate and collect finance data. We can classify Finance into Debt markets and Equity markets. These are further classified as public markets or private markets. Private market data are data regarding private transactions (sometimes also called Over the Counter or OTC transactions) and typically not publicly disclosed. Trade data and data on prices of goods, services, and commodities (such as price of a barrel of oil) are not considered as finance data at ALTADATA. Further, the data is segmented by geography of the trade or location of the exchange.
Finance Data at ALTADATA is data on a substantial subset of the US public equity markets. That is companies listed on NYSE or NASDAQ. All US registered public companies are required to submit certain filings about their operations, financial health, and provide data required to ensure fair practices. ALTADATA collects company data from the Securities and Exchange Commission (SEC) filings. There are more than 5000 publicly registered companies in the US exchanges. ALTADATA provides data on only the Russell 3000 companies. (Same as Russell 1000 and Russell 2000 companies combined.) These largest companies (approximately 3000 in count) comprise of more than 98% of the valuation of the total US market.
Who uses Finance Data? What are some use cases?
Finance data can be used for many different purposes. An economist may want to estimate trends in economic activity in a certain sector, say banking. Traders may want to benchmark companies based on fundamental data in their financial statements. Examples of this could be financial leverage and operating leverage. Financial analysts may use other ratios such as operating margin, price to earnings, debt to equity, and dividend payout to recommendations. Financial analysts can use growth data (revenue growth, earnings growth, etc.) to extrapolate future trends. Sector analysis can reveal clues into lifestyle changes and future trends.
What are typical Financial Data attributes?
Fundamental data from Balance Sheets, Income Statements, and Cash Flow Statements are the primary basis of our financial data. From daily closing stock prices and SEC reported data a plethora of financial indicators and factors can be calculated. In time dimension, year-over-year and quarter-over-quarter changes are reported. In terms of KPIs, many ratios are pre-calculated. And in terms of markets, price changes and volatility can indicate investor sentiment.
The primary data attributes are:
- Operating Expense
- SG&A Expense
- R&D Expense
- Operating income
- Interest Expense
- Tax provisions
- Net income
- Earnings per share
- Dividend Payout
- Cash and Equivalents
- Current Assets
- Total Assets
- Total Debt
- Total Liabilities
- Shareholder Equity
- Periodic Cash Flow in Operations
- Periodic Cash Flow in Financing Activities
- Periodic Cash Flow in Investment Activities
- Free Cash Flow
- Basic Shares
- Diluted Shares
- Closing Price
- Trade Volume
- Market Cap
- Market Sector
And many ratios and growth factors based on the above data.
How is Finance Data typically collected?
We collect and curate financial statement data from SEC data and report it in a standardized form. The advantage of this is so that companies can be compared based on features of their reported operations.
ALTADATA also collects and reports price and composition movements for certain market sectors and market indices in the US. These are S&P500 index, SPY, and SPDR ("Spider") sector ETFs for:
- Basic Materials
- Health Care
- Consumer Staples
- Consumer Discretionary
- Real Estate
What are the common challenges when buying Finance Data?
Financial Market Data is available from many sources. The primary questions are frequency, recency, reliability, coverage, and last but not least, price.
ALTADATA's objective is to provide reliable curated financial data with daily or weekly updates at a very reasonable price. Our frequency is typically daily or weekly. Our financial data is not suitable for day-trading or volatility trading. Our data is geared towards understanding fundamentals and long-term trends.