Asset Return Prediction via Machine Learning

Abstract

In this paper, we provide insights on the prediction of asset returns via novel machine learning methodologies. Machine learning clustering-enhanced classification and regression techniques to predict future asset return movements are proposed and compared. Numerical experiments show good applicability of the methodologies and backtesting unveils superior results in China A-shares markets.