Do Cross-Sectional Predictors Contain Systematic Information?

Journal of Financial and Quantitative Analysis, Forthcoming

45 Pages Posted: 5 Oct 2019 Last revised: 3 May 2022

See all articles by Joseph Engelberg

Joseph Engelberg

University of California, San Diego (UCSD) - Rady School of Management

R. David McLean

Georgetown University - Department of Finance

Jeffrey Pontiff

Boston College - Department of Finance

Matthew C. Ringgenberg

University of Utah - Department of Finance

Date Written: October 18, 2021

Abstract

Firm-level variables that predict cross-sectional stock returns, such as price-to-earnings and short interest, are often averaged and used to predict market returns. Using various samples of cross-sectional predictors and accounting for the number of predictors and their interdependence, we find only weak evidence that cross-sectional predictors make good time-series predictors, especially out-of-sample. The results suggest that cross-sectional predictors do not generally contain systematic information.

Keywords: Return predictability, data snooping, statistical bias, market risk premium.

JEL Classification: G00, G14, L3, C1

Suggested Citation

Engelberg, Joseph and McLean, R. David and Pontiff, Jeffrey and Ringgenberg, Matthew C., Do Cross-Sectional Predictors Contain Systematic Information? (October 18, 2021). Journal of Financial and Quantitative Analysis, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3459229 or http://dx.doi.org/10.2139/ssrn.3459229

Joseph Engelberg

University of California, San Diego (UCSD) - Rady School of Management ( email )

9500 Gilman Drive
Rady School of Management
La Jolla, CA 92093
United States

R. David McLean

Georgetown University - Department of Finance ( email )

3700 O Street, NW
Washington, DC Washington DC 20057
United States

Jeffrey Pontiff

Boston College - Department of Finance ( email )

Carroll School of Management
140 Commonwealth Avenue
Chestnut Hill, MA 02467-3808
United States

Matthew C. Ringgenberg (Contact Author)

University of Utah - Department of Finance ( email )

David Eccles School of Business
Salt Lake City, UT 84112
United States

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