Alpha Persistence Test

Alpha persistence testing is critical in insider-trading surveillance and quant scoring systems because regulators and portfolio managers must confirm that detected trading edges are not statistical artifacts. The test typically compares alpha coefficients (excess returns above benchmark) computed over rolling windows, using correlation analysis or regression stability tests to assess whether alpha remains positive and significant. High persistence indicates a robust, repeatable signal; low or negative persistence suggests the signal may reflect data mining bias, look-ahead bias, or market microstructure noise rather than genuine information advantage.

In the context of insider activity detection, alpha persistence testing guards against false positives by validating that clusters of abnormal insider transactions or suspicious trading patterns generate consistent alpha across different market regimes and time horizons. The test often incorporates breakpoint analysis to identify regime shifts and conditional persistence metrics that adjust for sector rotation, volatility regimes, or regulatory changes (such as blackout windows or trading plan amendments). A signal that persists only in specific regimes may indicate legitimate factor exposure rather than illegal information leakage, whereas true insider-driven alpha should demonstrate cross-regime stability.