About This Dashboard
Understanding our data sources, methodology, and the purpose behind the Fama-French Value Spread Analytics dashboard.
What is This Dashboard?
The Fama-French Value Spread Analytics dashboard is a free, educational resource designed to help investors, researchers, and students understand and track the historical behavior of factor premiums in equity markets. Our primary focus is on the "value spread": the monthly return difference between value and growth portfolios.
Comparing the latest monthly factor return with its own history gives researchers a way to judge how unusual that observation was. Percentiles and z-scores describe realized returns; they do not measure current stock valuations or establish the next period's expected return. The charts make that historical record easier to examine, including the periods when value portfolios lagged growth.
Our Mission: To democratize access to factor data and provide clear, accurate visualizations that help users understand the rich history of value investing and factor premiums.
Data Sources
All data on this dashboard is sourced from the Kenneth R. French Data Library, one of the most respected and widely-used sources of factor data in academic finance.
Methodology
Our analytics follow standard academic conventions for calculating and presenting factor data. Here's an overview of our methodology:
Value Spread Calculations
- HML (High Minus Low): The direct value factor return from Fama-French models, representing the spread between high and low book-to-market portfolios.
- B/M Spread: Alternative value spread using univariate book-to-market sorted portfolios (top quintile minus bottom quintile).
- Size-Value Interactions: Spreads within size buckets, such as Small Value minus Small Growth, allowing analysis of value effects across different market cap segments.
Statistical Measures
- Z-Scores: Standardized values showing how many standard deviations the current value is from the historical mean.
- Percentile Ranks: The percentage of historical observations that fall below the current value.
- Rolling Returns: Annualized returns over trailing windows (1, 3, 5, and 10 years) to show performance persistence.
- Distribution Statistics: Mean, median, standard deviation, skewness, and kurtosis of historical factor returns.
Data Updates
A scheduled job on the server checks the Kenneth R. French Data Library every night for a newly published month. When a new month appears, the job loads it and rebuilds the site's pages automatically. Since the library publishes monthly, usually a few weeks after month end, the site's newest data follows the library's release schedule.
Frequently Asked Questions
Return spreads show how value and growth portfolios performed relative to each other. Their history captures both gains and setbacks, which a long-run average can hide. Comparing a monthly return with that history helps explain the observation. It does not establish the stocks' present valuation or predict the next value premium.
We update our data periodically to match releases from the Kenneth R. French Data Library. Monthly factor returns are typically available with a 2-4 week lag.
For academic or professional research, we recommend accessing data directly from the Kenneth R. French Data Library to ensure accuracy and compliance with their terms of use. Our dashboard is intended for educational visualization purposes.
While the core three-factor data begins in July 1926, some datasets (like the five-factor model) are only available from July 1963 when additional data on profitability and investment patterns became available.
This dashboard is for educational and research purposes only. It should not be used as the sole basis for investment decisions. Factor investing involves risks, and past factor premiums may not continue in the future. Always consult with qualified financial professionals before making investment decisions.
The original 3-factor model (1993) includes market, size, and value factors. The 5-factor model (2015) adds profitability (RMW) and investment (CMA) factors, which help explain additional patterns in stock returns related to company quality and capital allocation decisions.
Academic Background
The factor models and data we use are based on groundbreaking academic research:
- Fama, E.F. & French, K.R. (1993). "Common risk factors in the returns on stocks and bonds." Journal of Financial Economics, 33(1), 3-56. - The foundational paper introducing the three-factor model.
- Fama, E.F. & French, K.R. (2015). "A five-factor asset pricing model." Journal of Financial Economics, 116(1), 1-22. - Extended the model with profitability and investment factors.
- Fama, E.F. & French, K.R. (1998). "Value versus Growth: The International Evidence." Journal of Finance, 53(6), 1975-1999. - Documented value premiums across global markets.
Eugene Fama was awarded the Nobel Prize in Economic Sciences in 2013 for his empirical analysis of asset prices, research that underpins the factor models used in this dashboard.
Who Operates This Site
This site is operated by Scott Jackson, sole proprietor. Ravenwood Capital Management is the business brand name used by Scott Jackson, sole proprietor.
The site is an independent, free educational resource. It is not affiliated with, endorsed by, or sponsored by Eugene Fama, Kenneth French, Dartmouth College, or the Kenneth R. French Data Library. We build visualisations and educational material on top of the publicly available data that the library publishes, and we document our calculations in full on the methodology page so that any figure shown here can be reproduced independently from the source files.
This site is educational and informational only. It does not provide personalised investment advice, does not make recommendations about specific securities, does not sell financial products, has no user accounts, and does not accept client funds or assets through this website. Publication of this site is not an offer or solicitation to provide investment advisory services, and no advisory relationship is created by reading it or by contacting us through it. The site is supported by on-page advertising.
Editorial standards. Every figure on this dashboard traces to the Kenneth R. French Data Library and is computed by published formulas. We do not estimate, interpolate, or fill gaps with modelled values. Where the evidence on a question is genuinely contested, as it is for the value premium and for factor timing, we describe the disagreement rather than pick a side, and we state plainly what the data cannot support.
Use the contact form to report a data discrepancy, ask about a calculation, or send feedback about the site.
Limitations and Disclaimers
Important Notice: This dashboard is provided for educational and research purposes only. The information presented here does not constitute investment advice, and no investment decisions should be made solely based on this data.
Past Performance: Historical factor returns do not guarantee future performance. Factor premiums can be negative for extended periods, and there is no assurance that historical patterns will continue.
Data Accuracy: While we strive for accuracy, users should verify critical data against original sources. We are not responsible for errors in data presentation or interpretation.
No Warranty: This dashboard is provided "as is" without warranty of any kind. Use at your own risk.