InsidersTradesSigma
Quantitative Signals & Scoring
A metric quantifying the strength of a predictive signal relative to random fluctuations or false positives in a quantitative scoring model.
In insider trading and market microstructure surveillance, the signal-to-noise ratio measures whether detected patterns in trading activity, transaction timing, or ownership changes represent genuine predictive information or statistical artifacts. Higher ratios indicate that anomalies flagged by the scoring system have greater explanatory power for subsequent price movement or enforcement risk, reducing false alert fatigue in compliance workflows.
Practitioners employ signal-to-noise analysis to filter quant scores by robustness, retain only high-conviction insights from form filing clusters or transaction concentrations, and calibrate pre-clearance decision thresholds. A deteriorating ratio may signal regime change, crowding of the alpha factor, or information decay, prompting model recalibration or factor orthogonalization.