Anomalies and False Rejections

66 Pages Posted: 14 Aug 2017 Last revised: 23 Jan 2020

See all articles by Tarun Chordia

Tarun Chordia

Emory University - Department of Finance

Amit Goyal

University of Lausanne; Swiss Finance Institute

Alessio Saretto

Federal Reserve Banks - Federal Reserve Bank of Dallas

Date Written: August 12, 2017


We use information from over two million trading strategies that are randomly generated using real data, and from strategies that survive the publication process to infer the statistical properties of the set of strategies that could have been studied by researchers. Using this set, we compute t-statistic thresholds that control for multiple hypothesis testing when searching for anomalies, at 3.84 and 3.38 for time-series and cross-sectional regressions, respectively. We estimate the expected proportion of false rejections that researchers would produce if they failed to account for multiple hypothesis testing to be 45.3%.

Keywords: Hypothesis testing, False discoveries, Trading strategies

JEL Classification: G10, G11, G12

Suggested Citation

Chordia, Tarun and Goyal, Amit and Saretto, Alessio, Anomalies and False Rejections (August 12, 2017). Swiss Finance Institute Research Paper No. 17-37, Available at SSRN: or

Tarun Chordia

Emory University - Department of Finance ( email )

Atlanta, GA 30322-2710
United States
404-727-1620 (Phone)
404-727-5238 (Fax)

Amit Goyal (Contact Author)

University of Lausanne ( email )

Batiment Extranef 226
Lausanne, Vaud CH-1015
+41 21 692 3676 (Phone)
+41 21 692 3435 (Fax)


Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4

Alessio Saretto

Federal Reserve Banks - Federal Reserve Bank of Dallas ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States

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