债市量化系列之六：如何优化量化模型的赔率与换手率：关键在仓位策略

Group 1: Report Industry Investment Rating - No information provided in the content Group 2: Core Viewpoints of the Report - Optimizing the position strategy can effectively enhance the real - world performance of the quantitative framework, which is a multiplier method for increasing returns, especially in volatile markets [2][6][111] - Binary full - position strategies can capture returns efficiently in obvious trends but come with high volatility, drawdown risks, and high turnover and commission costs; threshold step - by - step addition strategies have low trading frequency but limited ability to capture returns in volatile markets (except for the LG model) [2][111] - Single continuous strategies perform well in volatile markets. Linear and normal strategies show high return stability, while Sigmoid, Atanh, and Atanh - Sigmoid strategies have significant advantages in volatility control, suitable for risk - averse investors. The GRU model shows stable performance in improving odds, while the strategy advantages of LG, SVM and other models are environment - dependent [2][111] - In terms of turnover and commission consumption, single continuous strategies such as Sigmoid and Atanh can reduce turnover and commission consumption in volatile markets, and investors should focus more on returns rather than commission costs [2][111] Group 3: Summary According to the Table of Contents 3.1 Multi - factor Model's Position Strategy Introduction - Multi - long and short full - position strategy: It is a binary extreme position management mode, which can be used as a performance benchmark and a reference for other strategies. It performs poorly in bull markets and better in volatile markets, and is more suitable for non - linear models in volatile markets [12][32][33] - Threshold multi - long and short full - position strategy and step - by - step addition strategy: The threshold full - position strategy introduces a fuzzy interval filtering mechanism to reduce misjudgment risks and improve the overall risk - return ratio. The step - by - step addition strategy can reduce turnover and trading costs but may sacrifice some returns, except for the LG model in volatile markets [13][14][53] - Continuous strategies based on different risk preferences and mapping functions: Continuous strategies can convert binary probability signals into position adjustment signals, which can be divided into risk - seeking, risk - averse, and risk - neutral types according to risk preferences. Different mapping functions such as linear, Sigmoid, normal, Atanh, and Atanh - Sigmoid are used [18] 3.2 Strategy Back - testing - Back - testing sample interval and key parameters: The trading target is the Treasury bond futures T contract. The period from January 1, 2024, to December 31, 2024, is regarded as a bull market, and the period from January 1, 2025, to May 9, 2025, is regarded as a volatile market [31] - Benchmark results of multi - long and short full - position strategy: It has little effect on increasing returns in bull markets and performs better in volatile markets. Non - linear models such as RF and SVM can better handle the problem of return increase in volatile markets [33][34] - Threshold full - position strategy and step - by - step position adjustment strategy: The threshold strategy can optimize the odds of investment strategies in both bull and volatile markets, but the application effect depends on the model type and market environment. The step - by - step position adjustment strategy can significantly reduce turnover and trading costs but usually sacrifices some returns, except for the LG model in volatile markets [37][40][53] - Analysis of the effect of single continuous strategies: In volatile markets, continuous position strategies can significantly improve the odds of strategies without increasing the prediction win rate. Different strategies such as Atanh and Sigmoid have different risk - return characteristics, and their turnover is related to the model and market environment [58][73][74] - Rediscussion of the impact of trading commissions: The key is to increase returns rather than reduce costs. Although different models and strategies have different commission consumption, the impact of commissions on returns is relatively small, and investors should focus on return enhancement [94][97][110] 3.3 Summary and Strategy Recommendations - Different position management strategies play an important role in return acquisition and risk control. Investors should choose appropriate models and strategies according to their risk preferences and market conditions [111]