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Do Cross-Sectional Predictors Contain Systematic Information?

Published online by Cambridge University Press:  10 May 2022

Joseph Engelberg
Affiliation:
University of California, San Diego Rady School of Management jengelberg@ucsd.edu
R. David McLean
Affiliation:
Georgetown University, McDonough School of Business dm1448@georgetown.edu
Jeffrey Pontiff*
Affiliation:
Boston College, Carroll School of Management
Matthew C. Ringgenberg
Affiliation:
University of Utah, David Eccles School of Business matthew.ringgenberg@eccles.utah.edu
*
pontiff@bc.edu (corresponding author)
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Abstract

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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.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington
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