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Lucky Factors

74 Pages Posted: 22 Nov 2014 Last revised: 3 Oct 2017

Campbell R. Harvey

Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER); Duke Innovation & Entrepreneurship Initiative

Yan Liu

Texas A&M University, Department of Finance

Date Written: October 3, 2017

Abstract

We propose a new method to select amongst a large group of candidate factors -- many of which might arise as a result of data mining -- that purport to explain the cross-section of expected returns. The method is robust to general distributional characteristics of both factor and asset returns. We allow for the possibility of time-series as well as cross-sectional dependence. The technique accommodates a wide range of test statistics. Our method can be applied to both asset pricing tests based on portfolio sorts as well as tests using individual asset returns. In contrast to recent asset pricing research, our study of individual stocks fi nds that the original market factor is by far the most important factor in explaining the cross-section of expected returns.

Notes: This paper was formerly circulated under the title "How Many Factors?"

Keywords: Factors, Variable selection, Bootstrap, Data mining, Orthogonalization, Multiple testing, Predictive regressions, Fama-MacBeth, GRS, Performance evaluation, Return prediction

JEL Classification: G12, G14, C12, C21, C22, C31, C32

Suggested Citation

Harvey, Campbell R. and Liu, Yan, Lucky Factors (October 3, 2017). Available at SSRN: https://ssrn.com/abstract=2528780 or http://dx.doi.org/10.2139/ssrn.2528780

Campbell Harvey (Contact Author)

Duke University - Fuqua School of Business ( email )

Box 90120
Durham, NC 27708-0120
United States
919-660-7768 (Phone)
919-660-8030 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Duke Innovation & Entrepreneurship Initiative ( email )

215 Morris St., Suite 300
Durham, NC 27701
United States

Yan Liu

Texas A&M University, Department of Finance ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

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