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

45 Pages Posted: 22 Mar 2009 Last revised: 16 Oct 2013

See all articles by Zhijian (James) Huang

Zhijian (James) Huang

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

Multiple version iconThere are 2 versions of this paper

Date Written: February 15, 2009

Abstract

Previous studies show mixed results about the out-of-sample performance of various asset-pricing anomalies. To reduce data-snooping bias, this paper simulates a real-time trader who chooses among all asset-pricing anomalies published prior to that time using only non-forward-looking filters. I find that a trader can outperform the market by recursively picking the best past performer among published anomalies even after transaction costs are taken into account. The excess return tends to be highest when the trader looks at past performances between two years and five years and when the trader considers more anomalies. For published anomalies, their excess returns over benchmark as well as relative ranks among contemporaneous anomalies do not decrease over time, indicating a relatively stable performance once being published. Relying only on the then-available anomaly literature and historical data, the overall result shows a possible way to beat the market in real time.

Keywords: Data-snooping Bias, Asset-pricing Anomalies, Out-of-sample Test, Real-time Simulation

JEL Classification: G11, G14, D83

Suggested Citation

Huang, Zhijian, Real-Time Profitability of Published Anomalies: An Out-of-Sample Test (February 15, 2009). Available at SSRN: https://ssrn.com/abstract=1364813 or http://dx.doi.org/10.2139/ssrn.1364813

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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