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Anomaly Discovery and Arbitrage Trading

Published online by Cambridge University Press:  20 February 2023

Xi Dong ,
Qi Liu ,
Lei Lu ,
Bo Sun  and
Hongjun Yan Open the ORCID record for Hongjun Yan [Opens in a new window]
Xi Dong
Affiliation:
City University of New York Baruch College [email protected]
Qi Liu*
Affiliation:
Peking University Guanghua School of Management
Lei Lu
Affiliation:
University of Manitoba Asper School of Business [email protected]
Bo Sun
Affiliation:
University of Virginia Darden School of Business [email protected]
Hongjun Yan
Affiliation:
DePaul University Driehaus College of Business [email protected]
*
[email protected] (corresponding author)
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Abstract

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We analyze a model in which an anomaly is unknown to arbitrageurs until its discovery, and test the model implications on both asset prices and arbitrageurs’ trading activities. Using data on 99 anomalies documented in the existing literature, we find that the discovery of an anomaly reduces the correlation between the returns of its decile-1 and decile-10 portfolios. This discovery effect is stronger if the aggregate wealth of hedge funds is more volatile. Finally, hedge funds increase (reverse) their positions in exploiting anomalies when their aggregate wealth increases (decreases), further suggesting that these discovery effects operate through arbitrage trading.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 59 , Issue 3 , May 2024 , pp. 933 - 955
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank Thummim Cho (the referee) and Jennifer Conrad (the editor) for their constructive comments. We also thank Nick Barberis, Bruno Biais, Alon Brav, David Brown, Bjorn Eraker, Will Goetzmann, Michael Gofman, Paul Goldsmith-Pinkham, David Hirshleifer, Jon Ingersoll, Wenxi Jiang, Marcin Kacperczyk, Andrew Karolyi, Leonid Kogan, Andrew Lo, Benjamin Loos, Steve Malliaris, David McLean, Alan Moreira, Justin Murfin, Lubos Pastor, Anna Pavlova, Jeff Pontiff, Mark Ready, Jialin Yu, Jianfeng Yu, and seminar participants at Boston University, DePaul University, Georgetown University, HKUST, Johns Hopkins University, PBCSF Tsinghua University, Peking University, Rutgers, SAIF, Temple University, SEM Tsinghua University, University of Florida, University of Toronto, University of Virginia, University of Wisconsin Madison, Yale, the 2019 American Economic Association Meetings (AEA), the 2016 European Finance Association Meetings (EFA), the 2016 European Summer Symposium in Financial Markets, the 2015 China International Conference in Finance (CICF), and the 2015 Northern Finance Association Meetings (NFA) for helpful discussions. Lu is grateful for financial support provided by Bryce Douglas Chair in Corporate Finance. An earlier version of this article was circulated under the title “A Model of Anomaly Discovery.”

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