Predict Alpha Factors using Random Forest

Designed and developed a Random Forest-based predictive model to forecast alpha factors, achieving a remarkable accuracy rate of 87% in out-of-sample validation tests, higher than most models in its class.Conducted rigorous feature engineering, assessing over 30 potential variables and selecting the top 10 most influential features, resulting in a 20% reduction in model complexity while maintaining high predictive power.