Journal of Financial and Quantitative Analysis201651(4), f1-f5open access
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Journal of Financial and Quantitative Analysis201651(5), f1-f5open access
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Journal of Financial and Quantitative Analysis201651(5), b1-b8open access
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Journal of Financial and Quantitative Analysis201651(2), b1-b8open access
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Journal of Financial and Quantitative Analysis201651(1), b1-b7open access
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Journal of Financial and Quantitative Analysis201651(1), f1-f5open access
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Journal of Financial and Quantitative Analysis201651(3), f1-f5open access
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Journal of Financial and Quantitative Analysis201651(6), b1-b14open access
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Journal of Financial and Quantitative Analysis201651(3), b1-b7open access
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Review of Financial Studies201629(1), 5-68open access
Hundreds of papers and factors attempt to explain the cross-section of expected returns. Given this extensive data mining, it does not make sense to use the usual criteria for establishing significance. Which hurdle should be used for current research? Our paper introduces a new multiple testing framework and provides historical cutoffs from the first empirical tests in 1967 to today. A new factor needs to clear a much higher hurdle, with a t-statistic greater than 3.0. We argue that most claimed research findings in financial economics are likely false.