Fama-French Factor Exposure

Fama-French factor exposure quantifies how much of a portfolio's excess return derives from exposure to market beta, size premium (SMB), value premium (HML), profitability (RMW), and investment patterns (CMA). In insider-trading detection systems, elevated factor exposures that correlate with insider transaction timing reveal whether outperformance stems from public factor premiums or information advantage. A quant scoring engine uses factor decomposition to isolate abnormal returns attributable to material non-public information rather than systematic risk compensation.

For compliance and surveillance, tracking time-series stability of factor loadings around insider filing dates helps identify suspicious performance spikes. When an insider's account exhibits a sudden tilt toward high-value or high-profitability stocks immediately before positive earnings announcements, the Fama-French decomposition distinguishes legitimate factor timing from information leakage. This decomposition feeds directly into conviction scoring, conviction clustering, and signal persistence metrics to flag suspicious trading behavior masked by seemingly rational factor allocation.