Click here to flash read.
arXiv:2206.15365v3 Announce Type: replace
Abstract: I develop simple and intuitive bounds for the false discovery rate (FDR) in cross-sectional return predictability publications. The bounds can be calculated by plugging in summary statistics from previous papers and reliably bound the FDR in simulations that closely mimic cross-predictor correlations. Most bounds find that at least 75% of findings are true. The tightest bound finds at least 91% of findings are true. Surprisingly, the estimates in Harvey, Liu, and Zhu (2016) imply a similar FDR. I explain how Harvey et al.'s conclusion that most findings are false stems from equating "false" and "insignificant."
Click here to read this post out
ID: 809459; Unique Viewers: 0
Unique Voters: 0
Total Votes: 0
Votes:
Latest Change: March 29, 2024, 7:33 a.m.
Changes:
Dictionaries:
Words:
Spaces:
Views: 17
CC:
No creative common's license
No creative common's license
Comments: