By Rob Kozlowski|Mar. 1st, 2021
Ronen Israel, Bryan Kelly and Tobias Moskowitz were named winners of the $10,000 Harry M. Markowitz Award for their paper, “Can Machines ‘Learn’ Finance?”
The award was announced Feb. 25 by the Journal of Investment Management and New Frontier Advisors, co-sponsors of the award, in a joint statement.
The paper explores how asset management provides a unique set of challenges for machine learning that differ significantly from other practices in which machine learning has excelled.
The paper looks at the challenges and how critical it is for managers to develop realistic expectations for machine learning. The authors discuss potential pitfalls, beneficial use cases and emphasize “the importance of economic theory and human expertise for achieving success through financial machine learning,” according to the statement.
Mr. Israel is principal at AQR Capital Management; Mr. Kelly, professor of finance at Yale University and also principal at AQR Capital Management; and Mr. Moskowitz, professor of finance and economics at Yale University, research associate at NBER and also a principal at AQR Capital Management.
The awards, which recognize the impact of Mr. Markowitz’s work as a financial economist and mathematician in both theoretical and applied finance. Winners were selected by a panel of Nobel laureates in economics.
Also given special distinction awards with an honorarium of $5,000 each were Andrew W. Lo, Alexander Remorov and Zied Ben Chauch for their paper, “Measuring Risk Preferences and Asset-Allocation Decisions: A Global Survey Analysis,” and Robert C. Merton and Arun Muralidhar for their paper, “Six-Component Integrated Approach to Addressing the Retirement Funding Challenge.”
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This is a very interesting (short video) result in the normally breathless messages handed out recently by the machine learning promoters: Here is a URL to a video explaining the results of this work. Bryand Kelly starts out the video explaining why our normal view of machine learning is unlikely to yield positive results in the investment world. Towards the end, he divides the problem into some smaller sub-problems of the investing work that he thinks might yield to the abilities of machine learning. This is a relatively short 5 minute video worth your investment of time.
https://www.aqr.com/Learning-Center/Machine-Learning/Video-Introduction?gclid=CjwKCAjw6fCCBhBNEiwAem5SO_Gs7Usv87L0dzod5rMD_C4rCc87NkRaMk4LBQMVXcfdOHekdBcuPxoCVEwQAvD_BwE