Editor's Choice … and the Cross-Section of Expected Returns
提出新的多重检验框架，指出由于大量数据挖掘，新因子需达到t统计量大于3.0的更高门槛才能被认为显著，并认为金融经济学中多数声称的研究发现可能是错误的。
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. Received October 22, 2014; accepted June 15, 2015 by Editor Andrew Karolyi.