“…and the Cross-Section of Expected Returns”
written by Campbell R. Harvey (Duke University – Fuqua School of Business; National Bureau of Economic Research (NBER), Yan Liu (Duke University) and Heqing Zhu (Duke University – Fuqua School of Business). Posted on SSRN on October 4th.
“Hundreds of papers and hundreds of factors attempt to explain the cross-section of expected returns. Given this extensive data mining, it does not make any economic or statistical sense to use the usual significance criteria for a newly discovered factor, e.g., a t-ratio greater than 2.0. However, what hurdle should be used for current research? Our paper introduces a multiple testing framework and provides a time series of historical significance cut-offs from the first empirical tests in 1967 to today. Our new method allows correlation among the tests as well as publication bias. We also project forward 20 years assuming the rate of factor production remains similar to the experience of the last few years. The estimation of our model suggests that today a newly discovered factor needs to clear a much higher hurdle, with a t-ratio greater than 3.0. Echoing a recent disturbing conclusion in the medical literature, we argue that most claimed research findings in financial economics are likely false.”
Twitter profile of the month
Professor Patrick Dunleavy of LSE tweets and retweets daily on his account “Writing for research“: many relevant resources and thoughts!
See also his account on Medium: