… and the Cross-Section of Expected Returns

… и кросс-секция ожидаемых доходностей
Campbell R. Harvey, Yan Liu, Caroline Zhu
2015-10-09

cross-section of expected returnsdata mininghistorical cutoffs (1967–today)multiple testing frameworkt-statistic > 3.0
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. (JEL C12, C52, G12)
1
A new factor must have a t-statistic greater than 3.0 to clear the proposed higher significance hurdle.
2
A new multiple testing framework for evaluating asset pricing factors is introduced to set appropriate significance hurdles.
3
Given extensive data mining of hundreds of papers and factors, usual significance criteria are inappropriate.
4
Historical cutoffs for factor significance are provided, covering empirical tests from 1967 to the present.
5
The authors argue that most claimed research findings in financial economics are likely false under the new framework.

proposed asset pricing factors (candidate factors explaining the cross-section of expected returns)

Statistical significance thresholds and multiple-testing framework (historical cutoffs and required t-statistic threshold) for validating new factors explaining the cross-section of expected returns

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Publication Date
2015-10-09
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Authors
Campbell R. Harvey
Yan Liu
Caroline Zhu
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