Factor Regression
A few academic “factors” explain most of what any fund does. Regress any US ticker on them: market, size, value, profitability, investment, momentum. See what you really own, and whether any alpha is left.
About this tool
Run the regression the pros run: any US stock, ETF or fund against the Fama-French factors (market beta, size, value, profitability, investment, plus momentum) with alpha, t-statistics and R², on the same academic data used in the original research.
Factor regressions answer the most clarifying question in fund analysis: is this performance skill, or repackaged exposure? Most funds that look brilliant turn out to be ordinary loadings on value, size or momentum wearing a high fee, and true persistent alpha is genuinely rare once factors are accounted for.
What are the Fama-French factors?
Systematic return sources documented by Eugene Fama and Kenneth French: the market premium, size (small beats large historically), value (cheap beats expensive), profitability and investment patterns, with momentum added by Mark Carhart.
What does a significant alpha mean?
Return unexplained by factor exposures, with a t-statistic above roughly 2 suggesting it is unlikely to be luck. Sustained significant alpha is the rarest commodity in investing, which is exactly why the test matters.
What does R² tell me?
How much of the fund's movement the factors explain. An R² above 0.95 means you are essentially holding a factor portfolio, and should ask whether the fee reflects that.