Trends and Applications of Machine Learning in Quantitative Finance

Abstract

Recent advances in machine learning are finding commercial applications across many industries, not least the finance industry. This paper focuses on applications in one of the core functions of finance, the investment process. This includes return forecasting, risk modelling and portfolio construction. The study evaluates the current state of the art through an extensive review of recent literature. Themes and technologies are identified and classified, and the key use cases highlighted. Quantitative investing, traditionally a leading field in adopting new techniques is found to be the most common source of use cases in the emerging literature.

Keywords: Machine Learning, Quantitative Finance, Portfolio Construction, Return Forecasting

JEL Classification: C00, C1, C3, C5, C6, C8, 03, G1