Market Microstructure Noise

Market microstructure noise encompasses transient price deviations arising from mechanical trading mechanics, inventory management by market makers, and the discrete nature of order placement and execution. In insider trading surveillance and quantitative scoring platforms, distinguishing genuine insider signal from microstructure noise is critical, as high-frequency trading patterns, tick-size effects, and bid-ask bounce can generate false positives. Filtering techniques such as rolling-window volatility decomposition, mid-quote price normalization, and realized-spread adjustments help isolate economically meaningful price movements from ephemeral noise components.

From a risk perspective, unfiltered microstructure noise inflates signal-to-noise ratios and degrades the information coefficient of insider activity metrics, particularly for low-liquidity or thinly-traded securities where bid-ask spreads and order imbalance effects are most pronounced. Robust scoring systems employ multi-horizon filtering, participation-rate adjustments, and liquidity-weighted normalization to separate sustained insider accumulation from temporary order-book perturbations, thereby improving conviction-score reliability and reducing regulatory false alarms in compliance monitoring.