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Anomalies and false rejections

journal contribution
posted on 2020-05-01, 00:00 authored by Tarun ChordiaTarun Chordia, A Goyal, A Saretto
Abstract We use information from over 2 million trading strategies 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 3.8 and 3.4 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 about 45%.

History

Journal

Review of financial studies

Volume

33

Issue

5

Pagination

2134 - 2179

Publisher

Oxford University Press

Location

Oxford, Eng.

ISSN

0893-9454

eISSN

1465-7368

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

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