Real-Time Profitability of Published Anomalies: An Out-of-Sample Test

Quarterly Journal of Finance, Volume 3, Issue 3n4, 2013

40 Pages Posted: 17 Mar 2010 Last revised: 25 Aug 2014

Jing-Zhi Huang

Pennsylvania State University - University Park - Department of Finance

Zhijian (James) Huang

Rochester Institute of Technology (RIT) - Department of Accounting and Finance

Multiple version iconThere are 2 versions of this paper

Date Written: March 12, 2014

Abstract

Empirical evidence on the out-of-sample performance of asset-pricing anomalies is mixed so far and arguably is often subject to data-snooping bias. This paper proposes a method that can significantly reduce this bias. Specifically, we consider a long-only strategy that involves only published anomalies and non-forward-looking filters and that each year recursively picks the best past-performer among such anomalies over a given training period. We find that this strategy can outperform the equity market even after transaction costs. Overall, our results suggest that published anomalies persist even after controlling for data-snooping bias.

Keywords: Data-snooping Bias, Asset-pricing Anomalies, Out-of-sample Test, Published Anomalies

JEL Classification: G11, G14, D83

Suggested Citation

Huang, Jing-Zhi and Huang, Zhijian (James), Real-Time Profitability of Published Anomalies: An Out-of-Sample Test (March 12, 2014). Quarterly Journal of Finance, Volume 3, Issue 3n4, 2013. Available at SSRN: https://ssrn.com/abstract=1571706 or http://dx.doi.org/10.2139/ssrn.1571706

Jing-Zhi Jay Huang

Pennsylvania State University - University Park - Department of Finance ( email )

University Park, PA 16802
United States

HOME PAGE: http://www.personal.psu.edu/jxh56

Zhijian Huang (Contact Author)

Rochester Institute of Technology (RIT) - Department of Accounting and Finance ( email )

College of Business
105 Lomb Memorial Drive
Rochester, NY 14623-5608
United States

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