Anomalies and False Rejections

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Anomalies and False Rejections
Tarun Chordia
Goizueta Business School, Emory University
Amit Goyal
Swiss Finance Institute, University of Lausanne
Alessio Saretto
Jindal School of Management, University of Texas at Dallas
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%. Chordia2020.pdf (544.35 KB, 需要: 1 个论坛币)

2020-4-25 16:52:48 上传

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