Quantitative Trading System Based on Proximity Forest
By studying the application of the neighboring forest algorithm in stock trading,a trading signal classification model is obtained by combining the neighboring forest classification model with automated trading orders.Firstly,the classification model is combined with the in-dex moving average strategy to obtain a dual layer filtering model for trading signals.Then,the pricing strategy for automated orders,stock se-lection,and trading strategy for determining shares are determined through the average amplitude indicator and Kelly formula;Finally,the double-layer filtering model is combined with pricing and trading strategies to obtain a quantitative trading system based on the proximity for-est algorithm.Simulation experiments show that the average annual return rate of the system reaches 20.09%.Compared to the strategy relying solely on the exponential moving average,the neighboring forest algorithm has a more significant advantage in profitability.
proximity forestauto trading orderrisk managementtrading system
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