Skewness-Adjusted Return

In quantitative insider-trading detection and alpha-scoring frameworks, skewness-adjusted return captures the reality that two strategies with identical Sharpe ratios may carry dramatically different tail risks. A strategy generating steady gains punctuated by catastrophic insider-detected blow-ups exhibits negative skewness, violating the normality assumption underlying traditional metrics. By explicitly adjusting for the third moment of return distribution, quant platforms identify false-positive alpha signals that mask concentrated downside tail events, particularly relevant when surveillance flags anomalous trading clusters preceding adverse news.

The adjustment typically reduces headline returns when third moment is materially negative, implementing a penalty function scaled by estimated skewness coefficient. Within insider-activity concentration filters, this metric flags strategies where Form 4 filings precede volatile price reversals with asymmetric loss profiles. Risk governance models incorporate skewness-adjusted return thresholds to screen conviction scores and exclude alpha signals from quantile buckets exhibiting tail risk concentration that standard volatility-normalized metrics would overlook.