A Model of Anomaly Discovery

52 Pages Posted: 10 May 2015

See all articles by Liu Qu

Liu Qu

Independent

Lei Lu

Asper School of Business, University of Manitoba

Bo Sun

Board of Governors of the Federal Reserve System

Hongjun Yan

DePaul University

Date Written: May 8, 2015

Abstract

We analyze a model of anomaly discovery. Consistent with existing evidence, we show that the discovery of an anomaly reduces its magnitude and increases its correlation with existing anomalies. One new prediction is that the discovery of an anomaly reduces the correlation between deciles 1 and 10 for that anomaly. Using data for 12 well-known anomalies, we find strong evidence consistent with this prediction. Moreover, the correlation between deciles 1 and 10 of an anomaly becomes correlated with the aggregate hedge-fund wealth volatility after the anomaly is discovered. Our model also sheds light on how to distinguish between risk- and mispricing-based anomalies.

Keywords: Anomaly, Arbitrage, Discovery, Arbitrageur-based asset pricing

JEL Classification: G11, G23

Suggested Citation

Qu, Liu and Lu, Lei and Sun, Bo and Yan, Hongjun, A Model of Anomaly Discovery (May 8, 2015). Available at SSRN: https://ssrn.com/abstract=2604137 or http://dx.doi.org/10.2139/ssrn.2604137

Liu Qu

Independent ( email )

Lei Lu

Asper School of Business, University of Manitoba ( email )

181 Freedman Crescent
Winnipeg, Manitoba R3T 5V4
Canada

Bo Sun (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Hongjun Yan

DePaul University ( email )

1 East Jackson Blvd.
Chicago, IL 60604
United States

HOME PAGE: http://sites.google.com/site/hongjunyanhomepage/

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