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Statistical ArbitrageKalman FilterPythonFutures
Mean-Reversion Strategy for S&P 500 Futures
Developed a statistical arbitrage strategy exploiting mean-reverting behavior in S&P 500 E-mini futures using Kalman Filter for dynamic hedge ratio estimation and Ornstein-Uhlenbeck process for spread modeling.
1.87
Sharpe Ratio
2.34
Sortino Ratio
-8.2%
Max Drawdown
14.3%
CAGR
58.4%
Win Rate
1.72
Profit Factor
# Methodology
Applied cointegration analysis to identify statistically significant relationships between correlated assets. Implemented a Kalman Filter for real-time hedge ratio estimation, allowing the strategy to adapt to changing market conditions.
Core Model
# Data Source
EOD futures data from CME Group (2018-2024)