Research on Quantitative Investment Strategy Based on Random Forest Model and Risk Management

Abstract

Based on the significance of the information coefficient and the results of single factor back test, we select the optimal stock selection factor from the BP Factor Database and we construct the quantitative stock selection model by using the random forest algorithm. Then, we conduct a back test on the historical trading data of CSI300 index, compare the performance results of different risk management strategies, and finally choose the optimal quantitative investment strategy to select stocks based on the random forest model and carries out risk management based on a combination of position management with moving average and trailing