Parkinson Volatility Estimator

The Parkinson Volatility Estimator, introduced by Michael Parkinson in 1980, leverages the high-low range within a trading period to estimate volatility more efficiently than close-to-close returns. In insider-trading surveillance and quant scoring platforms, this estimator proves valuable because insider transactions often exhibit concentrated intraday price movements and elevated range dynamics. The measure is particularly sensitive to gaps and extreme moves that may signal coordinated trading or information leakage prior to material announcements.

Parkinson volatility integrates seamlessly into composite conviction indices and factor-exposure models by capturing tail risk and microstructure disturbances that close-based estimators miss. When combined with insider-activity concentration metrics and clustering analysis, it enhances detection of shadow trading, layering, and front-running patterns. The estimator's robustness to bid-ask bounce and its computational efficiency make it a standard component in real-time surveillance dashboards covering Form 4 filers and PDMR transaction reporters.