Research On Quantitative Trading Of Commodity Futures Based On Improved Turtle Strategy

After decades of rapid development,quantitative trading has gradually become an important way for global professional institutional investors.Domestic quantitative investment started late,but with the development of China’s capital market and the acceleration of global financial integration trend,China’s financial innovation is in the ascendant,new financial derivatives emerge in endlessly,quantitative investment related fields in China embarked on a rapid development period.Turtle trading strategy is one of the most classic quantitative strategies in the world.It uses the breakthrough of Donchian Channel as the main tool for judging trading signals,and realizes the purpose of cutting losses and running profits by virtue of flexible and effective position control and profit and loss stopping mechanism.The biggest advantage of the Turtle trading strategy is to track the trend market,and when the trend trend is smooth,it can generate very considerable profits.However,the tortoise trading strategy is also difficult to escape the inherent drawbacks of trend tracking strategy,that is,large-scale and long-term asset withdrawal and low winning rate.In this thesis,eight commodity futures with high market activity are selected as the empirical research objects for in-sample test according to the volume of transactions and positions.The retest cycle is 30 minutes high frequency data from January 2,2020 to December 31,2021.The retest results show that the performance of turtle trading strategies in different futures varieties is quite different,which is more suitable for metal futures with strong trend.Due to the best performance of the turtle trading strategy in Shanghai copper futures,this thesis takes Shanghai copper futures as an example,and conducts in-depth research and analysis from the perspectives of revenue and risk.In view of the defects of high withdrawal rate and low winning rate of the original Turtle trading strategy,this thesis puts forward the methods of strategy optimization :(1)Optimizing the strategy parameters according to the market environment;(2)Adding trend filtering module and introducing Kaufman adaptive averaging filter to optimize the opening conditions of trading system;(3)Based on the self-adaptive tracking stop line,the closing conditions are optimized,the original stop module of the system is deleted,and the percentage tracking stop line is replaced by the percentage tracking stop line.By adjusting the convergence parameters when the volatility is amplified,the tracking stop line becomes more sensitive,and more profits are retained to the maximum extent.Finally,the optimized turtle trading strategy is used for the out-of-sample test.The retest results show that the optimized strategy effectively filters the false breakthrough signal,and the winning rate is significantly improved.At the same time,the maximum asset withdrawal is significantly reduced,and the stability of strategic profit and risk control ability are significantly enhanced.