Beyond Beta: A Better Model of Returns
The Capital Asset Pricing Model (CAPM), developed in the 1960s, proposed that a single factor — beta, or sensitivity to the overall market — explained why some stocks delivered higher returns than others. Higher beta meant higher expected return, and that was largely the story.
By the late 1980s, researchers had accumulated substantial evidence that beta alone was a poor predictor of cross-sectional stock returns. Eugene Fama and Kenneth French's landmark 1992 paper, "The Cross-Section of Expected Stock Returns," published in the Journal of Finance, delivered the decisive challenge. They found that two additional characteristics — company size and book-to-market ratio — explained stock returns far better than beta.
The Size Factor (SMB)
Small-cap stocks — those with lower total market capitalisation — have historically delivered higher returns than large-cap stocks over long horizons. Fama and French called this the "size premium" and captured it with the SMB (Small Minus Big) factor: the return spread between small-cap and large-cap stocks.
Why? The risk-based explanation holds that small companies are more financially fragile, more sensitive to economic downturns, and less liquid — and investors demand a higher return as compensation for bearing these risks. The behavioural explanation suggests that large institutional investors systematically avoid small caps (due to capacity constraints), leaving them underowned and therefore underpriced.
The Value Factor (HML)
Stocks with low price-to-book ratios — so-called "value" stocks — have historically outperformed stocks with high price-to-book ratios ("growth" or "glamour" stocks). Fama and French captured this with the HML (High Minus Low) factor: the return spread between high book-to-market and low book-to-market stocks.
The risk-based interpretation: value companies are often financially distressed, and their higher expected returns compensate investors for taking on that distress risk. The behavioural interpretation: investors systematically overpay for growth stocks (extrapolating recent earnings growth too far into the future) and underpay for boring, low-growth companies.
The Five-Factor Extension
In 2015, Fama and French updated the model to include two additional factors: profitability (profitable firms outperform unprofitable ones, all else equal) and investment (firms that invest conservatively outperform those that invest aggressively). This five-factor model captures even more of the variation in stock returns, though it also attracted criticism for being increasingly data-driven rather than theoretically grounded.
Risk or Mispricing?
The debate over whether factor premiums represent compensation for risk or evidence of systematic behavioural error remains unresolved. In practice, it may not matter much for the investor: if the premium is real and persistent, capturing it is valuable regardless of its source. What does matter is whether the premium survives after costs and whether it persists once widely known and traded.