Lei Yang

Machine learning-driven financial time series forecasting: application of a feature engineering-enhanced RF model in A-share energy stocks

This study proposes a dual-path optimized RF framework for closing price forecasting of 6 A-share energy leaders, introducing a two-stage feature screening mechanism combining Spearman rank correlation and permutation feature importance, and further embed ensemble pruning to remove low-contribution sub-trees from the R...