InsidersTradesSigma
Performance & Risk Metrics
A non-parametric volatility estimator that uses high, low, and close prices to measure intraday price dispersion without requiring opening prices, making it robust to overnight gaps and useful for evaluating strategy execution quality in insider-trading detection models.
Rogers-Satchell volatility, developed by Rogers and Satchell in 1991, estimates realized volatility from the logarithmic range of high-low-close prices. Unlike classical Parkinson or Garman-Klass estimators, it avoids dependence on opening prices, which makes it particularly valuable when analyzing equity trades occurring outside regular trading hours or when detecting suspicious trading patterns around material nonpublic information disclosures. The measure is especially useful in quant scoring platforms where transaction timing and price discovery mechanics inform insider-activity detection algorithms.
In the context of insider-trading surveillance, Rogers-Satchell volatility serves as a baseline for assessing whether observed trading activity generated abnormal price impact relative to contemporaneous market microstructure. By isolating intraday volatility independent of opening prices, compliance teams and quantitative investigators can distinguish genuine liquidity-seeking behavior from coordinated or informed trades that exploit temporary information asymmetries. The estimator also normalizes signal strength across different market regimes and securities with heterogeneous trading patterns.
Formula