Financial Machine Learning

161 Pages Posted: 26 Jul 2023

See all articles by Bryan T. Kelly

Bryan T. Kelly

Yale SOM; AQR Capital Management, LLC; National Bureau of Economic Research (NBER)

Dacheng Xiu

University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER)

Multiple version iconThere are 3 versions of this paper

Date Written: July 24, 2023

Abstract

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping machine learning tools, as well as for statisticians and machine learners seeking interesting financial contexts where advanced methods may be deployed.

JEL Classification: C33,C4,C45,C55,C58,G1,G10,G11,G12,G17

Suggested Citation

Kelly, Bryan T. and Xiu, Dacheng, Financial Machine Learning (July 24, 2023). University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2023-100, Available at SSRN: https://ssrn.com/abstract=4520856 or http://dx.doi.org/10.2139/ssrn.4520856

Bryan T. Kelly

Yale SOM ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

AQR Capital Management, LLC ( email )

Greenwich, CT
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Dacheng Xiu (Contact Author)

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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