Investment research can draw on a variety of free investment data sources. Whether you are testing a factor strategy, estimating intrinsic value, analyzing market history or building a investing project in Python code, the data source you choose can affect your conclusions.
Fortunately, investors and researchers can access a wide range of free or largely free datasets from academic institutions, asset managers, government agencies and financial websites.
Some widely available free investment data sources include:
- Ken French’s Fama-French Data Library (LINK)
- Robert Shiller’s historical market datasets (LINK)
- Aswath Damodaran’s valuation data (LINK)
- Federal Reserve Economic Data, commonly known as FRED (LINK)
- Yahoo! Finance (LINK)
- Cliff Asness and AQR (LINK)
Each source is a unique investor resource. Some are ideal for academic research, while others are better suited to company analysis, market prices or macroeconomic reviews. We offer a review of each source, along with key datasets and the link to the site.
1. Fama-French Data Library
The Fama-French Data Library is maintained by Ken French at Dartmouth College and is an invaluable resource for factor research.
The library provides downloadable, free investment data related to the Fama-French asset-pricing models, including:
- Market excess returns
- Small-cap versus large-cap returns (known as SMB)
- Value versus growth returns (known as HML)
- Profitability factors (known as RMW)
- Investment factors (known as CMA)
- Momentum portfolios
- Size and book-to-market portfolios
Professors Fama and French created the three-factor model, which expanded the traditional Capital Asset Pricing Model (CAPM) by adding size and value factors. The Professors later added profitability and investment, and they continue to publish data for both the three- and five-factor models.
We think Fama-French data is especially useful for factor investing research, academic projects and estimating factor exposures.
2. Robert Shiller’s Historical Free Investment Data
Professor Robert Shiller’s market datasets are among the most valuable free investment data sources for long-term U.S. market research. The core dataset contains monthly information beginning in January 1871, including:
- Stock prices
- Dividends
- Earnings
- Consumer Price Index (CPI)
- Long-term interest rates
- The cyclically adjusted price-to-earnings ratio (CAPE)
The CAPE ratio compares the market price with average inflation-adjusted earnings over approximately ten years. It is commonly used to study long-term market valuation and expected returns.
We like the Shiller dataset for long-term market research, as well as analyses pertaining to historical dividends and earnings growth.
3. Cliff Asness and AQR Data
AQR Capital Management publishes a useful collection of free datasets related to factor investing and systematic strategies. Many of the datasets are associated with research by Cliff Asness and other AQR researchers.
Available datasets include research on:
- Value
- Momentum
- Quality
- International equity factors
- Quality Minus Junk
AQR’s resources are particularly useful for investors who want to study factor definitions and reproduce published research. The accompanying papers are important because they explain how the portfolios were formed, which securities were included, and how returns were calculated.
We use AQR’s datasets for factor and model research, momentum analysis, quality review and appreciate the commentaries Mr. Asness writes.
4. Aswath Damodaran’s Free Investment Data
Aswath Damodaran, a professor at New York University’s Stern School of Business, provides a large collection of valuation data, spreadsheets, teaching materials, and corporate-finance tools.
His datasets cover areas such as:
- Equity risk premiums
- Country risk premiums
- Historical returns
- Cost of capital
- Price-to-earnings ratios
- Price-to-book ratios
Damodaran’s current datasets are organized by geography, including the United States, Europe, Japan, Canada, Australia, New Zealand, emerging markets, and global markets. His website also provides archived datasets for historical comparisons. The data page states that the main datasets are generally updated during the first two weeks of each year, while some risk-premium datasets may be updated more frequently.
We find Professor Damodaran’s resources are especially useful for estimating the cost of equity, comparing companies by industry, estimating country risk premiums and comparing valuation multiples.
5. Yahoo! Finance
Yahoo Finance is a convenient source of free investment data for market prices, corporate information, dividends, stock splits, financial statements, options data, exchange-traded funds, and basic company statistics.
It is commonly used for:
- Historical stock prices
- Adjusted closing prices
- Dividends
- Market indexes
We like Yahoo! Finance’s easy-to-access historical data. The quality rivals other more expensive options and for DIY investors, can be more than sufficient for quick modeling or historical data projects.
For coding projects, the open-source `yfinance` Python package is oft-cited as a way to retrieve Yahoo! Finance data. It supports ticker information, historical prices, multiple-ticker downloads, sector and industry information, options and screening features.
6. FRED: Federal Reserve Economic Data
FRED is one of the best free investment data sources for macroeconomic and financial time series.
The platform provides thousands of series covering:
- Inflation
- Gross domestic product
- Unemployment
- Interest rates
- Treasury yields
- Money supply
- Consumer sentiment
- Recessions
Popular series include the Consumer Price Index, the unemployment rate, the Federal Funds Rate, the 10-year Treasury yield, real GDP and the S&P 500 index.
FRED data can be downloaded through the website in CSV and Excel formats. Users can also create dashboards, save charts, build data lists, and access data programmatically through the FRED API.
We like FRED data for direct access to macroeconomic, interest rate, inflation and other datasets for quantitative modeling work.
Final Thoughts on Sources for Free Investment Data
Selecting an investment data source depends on the question you are trying to answer. There isn’t one-stop shopping for investment data, even for institutional investors. Thus, having a strong go-to set of databases is critical.
We’d summarize the aforementioned resources as follows: Fama-French is a strong in factor research. Shiller is valuable for studying long-term market valuation and CAPE. AQR provides practical datasets for systematic investing research. Damodaran offers valuation and industry resources. Yahoo! Finance is convenient for market prices and company-level exploration, while FRED is an essential source for economic and interest-rate data.
Used together, these resources can support a robust research process.
Important Information
This article is provided for educational and informational purposes only. There can be no assurance that any investment research or the use of these resources will result in profitable investment outcomes.
The third-party websites, data sources, and other resources referenced or linked in this article are provided for informational purposes and convenience. We do not control these third-party resources and do not independently verify or guarantee the accuracy, completeness, timeliness, or continued availability of their data or content.
Third-party websites and resources may change, become unavailable, or contain information that is inaccurate or incomplete. Use of third-party data and resources is at the reader’s discretion, and readers should evaluate the information and its suitability for their intended purpose.
