TITLE:
Asset Return Prediction via Machine Learning
AUTHORS:
Liangliang Zhang
KEYWORDS:
Clustering, Classification, Regression, Unsupervised Learning, Supervised Learning, Deep Neural Networks, Machine Learning, Asset Returns, Prediction, Investment Strategies, Universal Approximation Theorem
JOURNAL NAME:
Journal of Mathematical Finance,
Vol.9 No.4,
October
30,
2019
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.