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The Review of Asset Pricing Studies Vol. 10 No. 2 2020

An Evaluation of Alternative Multiple Testing Methods for Finance Applications

Campbell R. Harvey1; YAN LIU2; Alessio Saretto3

1 Duke University, National Bureau of Economic Research · 2 Purdue University · 3 University of Texas at Dallas

open access

Abstract

In almost every area of empirical finance, researchers confront multiple tests. One high-profile example is the identification of outperforming investment managers, many of whom beat their benchmarks purely by luck. Multiple testing methods are designed to control for luck. Factor selection is another glaring case in which multiple tests are performed, but numerous other applications do not receive as much attention. One important example is a simple regression model testing five variables. In this case, because five variables are tried, a t-statistic of 2.0 is not enough to establish significance. Our paper provides a guide to various multiple testing methods and details a number of applications. We provide simulation evidence on the relative performance of different methods across a variety of testing environments. The goal of our paper is to provide a menu that researchers can choose from to improve inference in financial economics.

DOI
10.1093/rapstu/raaa003
Volume
10
Issue
2
Pages
199-248
Language
en
Sources
crossref bibtex:phds-export.bib openalex

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