SSRNPortfolio & Allocation

Machine Learning Approach for Predicting U.S. ETFs’ Tracking Errors – Implications on U.S. Invested Fund

Machine learning methods, specifically Random Forest and Gradient Boosting Decision Tree, are found to be more effective in predicting U.S. ETF’s tracking errors, with U.S. assets and expense ratio being key factors.