Many charts on Passerine Finance compare stocks with something else — with inflation, with bonds, with cash, or with different ways of investing over time. Every one of them needs the same thing underneath: a single, consistent record of how the U.S. stock market has behaved over the years. This page explains the record we use.
We use the U.S. market-return series built from the Fama/French research data, published by the Kenneth R. French Data Library at Dartmouth College. It is a broad measure of the U.S. stock market.
The dataset
What are the Fama/French data?
Eugene Fama and Kenneth French are two well-known economists who put together data on how U.S. stocks have performed over time. Their Data Library, hosted at Dartmouth College, has become one of the most trusted and widely used records of stock-market history in finance.
What makes it useful to us is its reach. Rather than following a short list of big-name companies, the data track a broad slice of the whole U.S. stock market — which makes it a good, even-handed gauge of how "the market" as a whole has done. The dataset reports a few different figures, but the one that matters for our charts is simple: the overall return of that broad basket of U.S. stocks, month by month.
The calculation
How we calculate the market return.
The data split the market's return into two parts: the return above a safe baseline rate (labeled Mkt-RF) and that safe baseline rate itself (labeled RF — the "risk-free" return you'd earn on short-term U.S. Treasury bills). To get the market's full return, we just add the two back together.
What it represents
A broad slice of the U.S. market.
The Fama/French U.S. market factor represents a broad, value-weighted portfolio of eligible U.S. stocks, built for financial research. "Value-weighted" simply means larger companies have more influence on the result than smaller ones.
According to the official methodology, the market return is the value-weighted return of all firms incorporated in the U.S. and listed on the NYSE, AMEX, or NASDAQ that meet the dataset's inclusion rules. That universe is broader than the S&P 500: it is designed to represent the U.S. equity market as a whole, not a list of exactly 500 large companies.
It is also a total-return series. The returns are built from underlying data that includes both dividends and price changes, so the numbers reflect what owning stocks actually returned — not just price movement with dividends left out.
Building the chart
How we create a "Growth of $100" line.
The dataset gives a return for each period, not a running index level. To draw money growing, we compound those returns. Starting from $100, each period's value is the previous value grown by that period's return:
We use the monthly Fama/French data, so we compound month after month, starting from $100 just before the first month (July 1926). The resulting "Growth of $100" line is created by Passerine Finance — a derived series, not an official index published by Fama, French, Dartmouth College, or any index provider.
Why not the S&P 500
A note on the S&P 500.
The S&P 500 is a useful, widely followed index of about 500 large U.S. companies, and we reference it elsewhere on the site. For our purpose it serves much the same role as the Fama/French series — a stand-in for "the U.S. stock market." The practical difference is ownership: the S&P 500 is a proprietary commercial index from S&P Dow Jones Indices, and republishing its historical values would require a license. The Fama/French research data give us a broad, well-documented market series we can use openly, with attribution, so that's what we build on.
Source: Kenneth R. French Data Library, Dartmouth College, "Fama/French Research Data Factors." Passerine Finance calculates the U.S. market return as Mkt-RF plus RF and compounds those returns to create its derived growth series.
Usage & legal
Attribution and usage.
The Kenneth R. French Data Library makes these research datasets available for download and documents how they're built. We use the data for educational charts and calculations, attribute the source, and clearly separate the source data from our own derived work. We don't claim ownership of the underlying Fama/French data, and we don't imply endorsement by Eugene Fama, Kenneth French, Dartmouth College, CRSP, or any related organization. Our "Growth of $100" series is a derived educational calculation, not an official market index.
The Data Library publicly provides these datasets for download and documents their construction, but does not appear to publish a simple Creative Commons–style license covering every downstream use. We therefore use the data with clear attribution and identify our own calculations, without implying sponsorship or endorsement. This describes our data practices and is not legal advice; attribution alone does not resolve every possible copyright, database-right, or contractual question.
Citing this data
How we cite it.
For consistency, here is the wording we use across the site.
Short: Kenneth R. French Data Library, "Fama/French Research Data Factors," Dartmouth College. U.S. market return calculated by Passerine Finance as Mkt-RF + RF.
Chart-sized: Source: Kenneth R. French Data Library; calculations by Passerine Finance.
Full methodology note: Historical U.S. stock-market returns are derived from the Fama/French Research Data Factors from the Kenneth R. French Data Library. Passerine Finance calculates the market return as Mkt-RF plus RF and compounds the resulting periodic returns to create a hypothetical growth series. This series is not the S&P 500 or an official investment index.
The takeaway
Why it fits.
The Fama/French market series isn't a perfect substitute for every market index, and it isn't meant to be. It gives Passerine Finance a consistent, broad, research-oriented measure of historical U.S. stock-market returns — well suited to teaching long-term investing, risk, inflation, and compounding.
About this page
Dataset: Fama/French Research Data Factors (3 Factors), monthly, from the Kenneth R. French Data Library. Market return = Mkt-RF + RF, compounded from $100 to build the growth series. Coverage begins July 1926. Figures are educational; historical returns do not predict future performance, and this page is not investment or legal advice.