Alternative Thinking

Can Machines "Learn" Finance?

2Q19

Topics - Machine Learning

Read Time - 10min

${ numberSection } ${ text }
Can Machines "Learn" Finance?

Can machine learning be helpful to asset management – and if so, how? Asset markets fundamentally differ from many of the environments in which machine learning has enjoyed success, and research into machine learning for asset management is just beginning.

In this Alternative Thinking, we discuss the crucial points for understanding the current state of machine learning in the practice of asset management:

  • How machine learning attempts to solve difficult problems and how it differs from traditional computer programming.
  • Why finance poses unique challenges even for the most powerful machine learning programs
  • Early research evidence hints that machine learning tools can potentially improve investment portfolios

The application of machine learning techniques is a natural evolution for investment research, and one that will continue to be explored.

 

 


About the Portfolio Solutions Group

The Portfolio Solutions Group (PSG) aims to help AQR clients achieve better portfolio outcomes and provide unique insights to the broader investment community.


We thank Bryan Kelly, Ronen Israel and Tobias Moskowitz for their work on this paper. We also thank Gregor Andrade, Pete Hecht, Antti Ilmanen, Michael Katz, Lasse Pedersen and Dan Villalon for their helpful comments.

AQR Capital Management, LLC, (“AQR”) provide links to third-party websites only as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by us of any content or information contained within or accessible from the linked sites. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which AQR.com has no control. In no event will AQR be responsible for any information or content within the linked sites or your use of the linked sites.

 

The information contained herein is only as current as of the date indicated, and may be superseded by subsequent market events or for other reasons. The views and opinions expressed herein are those of the author and do not necessarily reflect the views of AQR Capital Management, LLC, its affiliates or its employees. This information is not intended to, and does not relate specifically to any investment strategy or product that AQR offers. It is being provided merely to provide a framework to assist in the implementation of an investor’s own analysis and an investor’s own view on the topic discussed herein. Past performance is not a guarantee of future results.

 

Hypothetical performance results have many inherent limitations, some of which, but not all, are described herein. Hypothetical performance results are presented for illustrative purposes only.

 

Diversification does not eliminate the risk of experiencing investment loss.

 

Certain publications may have been written prior to the author being an employee of AQR.

This material is intended for informational purposes only and should not be construed as legal or tax advice, nor is it intended to replace the advice of a qualified attorney or tax advisor.