Can Machines 'Learn' Finance?

Journal of Investment Management

21 Pages Posted: 2 Jul 2020 Last revised: 5 Mar 2021

See all articles by Ronen Israel

Ronen Israel

AQR Capital Management, LLC

Bryan T. Kelly

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

Tobias J. Moskowitz

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

Date Written: January 10, 2020

Abstract

Machine learning for asset management faces a unique set of challenges that differ markedly from other domains where machine learning has excelled. Understanding these differences is critical for developing impactful approaches and realistic expectations for machine learning in asset management. We discuss a variety of beneficial use cases and potential pitfalls, and emphasize the importance of economic theory and human expertise for achieving success through financial machine learning.

Suggested Citation

Israel, Ronen and Kelly, Bryan T. and Moskowitz, Tobias J., Can Machines 'Learn' Finance? (January 10, 2020). Journal of Investment Management, Available at SSRN: https://ssrn.com/abstract=3624052 or http://dx.doi.org/10.2139/ssrn.3624052

Ronen Israel

AQR Capital Management, LLC ( email )

Greenwich, CT
United States

Bryan T. Kelly (Contact Author)

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

Tobias J. Moskowitz

Yale University, Yale SOM ( email )

New Haven, CT 06520
United States

HOME PAGE: http://som.yale.edu/tobias-j-moskowitz

AQR Capital ( email )

Greenwich, CT
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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