Prediction of Returns of Taiwan 50 Index Constituents Using Random Forest Algorithm

This research takes the constituent stocks of FTSE TWSE Taiwan 50 Index as the forecasting targets and uses the random forest algorithm and regression tree to predict the return rate for each quarter. The testing period is from December 23, 2019 to December 17, 2021. The total model-constructing period is from June 22, 2015 to June 18, 2021. After feature collection and expansion, feature screening, and parameter adjustment, the model was completed according to different trained seasons, and we discussed the main reasons for the success of the model. The empirical results show that the high explanatory ability of the model needs to consider the fluctuation range of the reward during the trained period and the return fluctuation during the targeting period.