The three factors
The Fama-French model states: Expected excess return = β₀(Rm−Rf) + β₁(SMB) + β₂(HML), where SMB (Small Minus Big) is the return of small-cap stocks minus large-cap stocks and HML (High Minus Low) is the return of value stocks minus growth stocks. Each factor is a zero-cost portfolio: SMB is long small-caps and short large-caps; HML is long high book-to-market stocks and short low book-to-market stocks. A stock’s loading on each factor (its beta to that factor) determines how much of its expected return can be attributed to each risk source. A small-cap value stock has high loadings on both SMB and HML and thus has higher expected returns — but also higher expected risk.
Risk-based vs behavioural explanations
The debate over why these factors exist is one of the most contested in finance. The risk-based explanation (Fama and French’s preferred view) holds that small-cap and value stocks are genuinely riskier in ways CAPM does not fully capture — they are more exposed to economic downturns, financial distress, and illiquidity. Higher returns compensate for this higher risk. The behavioural explanation holds that value stocks are cheap because investors systematically overweight recent earnings disappointments (extrapolating poor short-term performance too far into the future), creating mispricing that rational investors can exploit. The empirical evidence does not cleanly resolve the debate — both forces probably contribute.
The five-factor extension
Fama and French extended the model in 2015 to five factors, adding RMW (Robust Minus Weak, the profitability factor) and CMA (Conservative Minus Aggressive, the investment factor). Highly profitable firms outperform (a finding consistent with quality-focused investing). Firms that invest conservatively (low capital expenditure relative to assets) outperform aggressive investors. The five-factor model explains return dispersion even more effectively — but it rendered HML largely redundant in the presence of profitability and investment factors, a finding Fama and French themselves acknowledge. AQR’s Carhart model added a momentum factor, creating a widely-used four-factor model (market + size + value + momentum).
“The Fama-French factors were an empirical discovery first and a theory second. The industry built around them is now larger than many of the markets the model was designed to describe.”
What this means for you
The Fama-French model is the intellectual foundation for factor-based or "smart beta" investing — a major segment of the ETF market. If you invest in a small-cap value ETF, you are explicitly tilting your portfolio toward the SMB and HML factors. Understanding the model helps you evaluate whether these tilts are genuinely compensated risk factors (as Fama and French argue) or partially behavioural mispricings — the distinction matters because the latter may diminish as more capital chases the anomaly. The post-publication performance of the value factor has been weaker than its historical average, fuelling ongoing debate about whether smart beta products deliver the factor premiums their marketing materials promise.