Research on Pairs Trading Strategy Based on Generalized Hurst Exponent and Ant Colony Optimization Algorithm
This study focuses on eight metal futures contracts listed on the Shanghai Futures Exchange.Initially,leveraging traditional cointegration theory and a first-order generalized Hurst exponent meth-od,futures pairs demonstrating robust mean-reverting characteristics are identified as optimal pairs for trading.Subsequently,trading strategies are devised for the selected optimal pairs,employing an ant colony optimization algorithm to determine the optimal opening thresholds for long-short trading.During the empirical back-testing phase,the research utilizes a sliding window approach for multiple in-sam-ple and out-of-sample backtests on historical data,comparing the results with traditional fixed thresh-old strategies based on mean and standard deviation.The findings reveal that the steel rebar-HRC and HRC-aluminum futures pairs are the best combinations for different sample periods.In terms of trading performance,the strategy employing the ant colony optimization algorithm to determine the opening thresholds outperforms traditional threshold strategies,achieving higher annualized returns and Sharpe ratios for long-short trading.
万方数据
维普
