Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?

Yu-Chin Hsu, Hsiou-Wei Lin () and Kendro Vincent ()
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Hsiou-Wei Lin: Department of International Business National Taiwan University, http://www.management.ntu.edu.tw/en/IB
Kendro Vincent: Department of International Business National Taiwan University, http://www.management.ntu.edu.tw/en/IB

No 17-A003, IEAS Working Paper : academic research from Institute of Economics, Academia Sinica, Taipei, Taiwan

Abstract: This study examines the possible data-snooping bias as a competing explanation for the anomalies in the cross-section of stock returns. We posit that the exhaustive standalone searches for profitable strategies could lead to recommending spuriously predictive variables. In order to explore the severity of this problem, we use a multiple testing method to evaluate the profitability of portfolios constructed by these predictors. Our empirical analyses suggest that over half of the findings based on individual testing method are no longer statistically significant after we adjust for data-snooping bias. Excluding the micro-cap stocks before portfolios construction and applying the notion of economic significance in this study further weaken the evidence for predictability. JEL Classification: G11, G12, G14

Keywords: anomalies; data-snooping bias; stock return predictability; portfolio strategies (search for similar items in EconPapers)
Pages: 40 pages
Date: 2017-01
New Economics Papers: this item is included in nep-fmk
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Citations: View citations in EconPapers (1)

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