Dynamic Hedge Ratio Estimation Using Kalman Filtering in Pairs Trading

This paper explores the application of Kalman Filter for dynamic hedge ratio estimation in pairs trading strategies. We demonstrate improved performance over static OLS regression by allowing the hedge ratio to adapt to changing market conditions. Backtesting on US equity pairs shows a 23% improvement in Sharpe ratio compared to traditional cointegration-based approaches.