Sentiment Reversal Propensity

Sentiment Reversal Propensity quantifies the mean-reversion tendency embedded in insider trading signals by analyzing historical patterns of conviction decay and behavioral correction. Unlike static sentiment scores, this metric explicitly models the temporal trajectory of insider positioning, accounting for the fact that extreme bullish or bearish conviction by insiders often precedes tactical reversals as information asymmetries compress or market conditions shift. The propensity is calibrated using rolling look-back windows and cross-validated against realized reversals in Form 4 filings and trading plan amendments.

The propensity score incorporates signal persistence metrics, conviction clustering patterns, and information-coefficient decay to distinguish between durable conviction signals and mean-reverting noise. A high propensity score indicates elevated risk of sentiment reversal, typically observed when insiders have accumulated extreme long or short positions relative to their historical trading ranges, or when conviction concentrations emerge among a narrow peer group. Integration with pre-clearance systems and blackout window calendars enables real-time adjustment of factor exposure, reducing drawdowns during predicted reversal episodes.