Missing Data in Asset Pricing Panels

64 Pages Posted: 18 Nov 2021

See all articles by Joachim Freyberger

Joachim Freyberger

University of Bonn; University of Wisconsin - Madison

Björn Höppner

University of Bonn - Department of Economics

Andreas Neuhierl

Washington University in St. Louis - John M. Olin Business School

Michael Weber

University of Chicago - Finance; National Bureau of Economic Research (NBER)

Date Written: September 28, 2021

Abstract

Missing data for return predictors is a common problem in cross sectional asset pricing studies. Most papers do not explicitly discuss how they treat missing data but conventional treatments focus on complete cases for all predictors or impute the unconditional mean for the missing predictor. Both methods have undesirable properties - they are either inefficient or lead to biased estimators and incorrect inference. We propose a simple and computationally attractive alternative approach using conditional mean imputations and weighted least squares. This method allows us to use all sample points with observed returns, it results in valid inference, and it can be applied in non-linear and high-dimensional settings. We map our estimator into a GMM framework to study its relative efficiency and find that it performs almost as well as the efficient but computationally costly GMM estimator in many cases. We apply our procedure to a large panel of return predictors and find that it leads to improved out-of-sample predictability.

Keywords: Cross Section of Returns, Missing Data, Expected Returns, Generalized Method of Moments

JEL Classification: C14, C58, G12

Suggested Citation

Freyberger, Joachim and Freyberger, Joachim and Höppner, Björn and Neuhierl, Andreas and Weber, Michael, Missing Data in Asset Pricing Panels (September 28, 2021). Available at SSRN: https://ssrn.com/abstract=3932438 or http://dx.doi.org/10.2139/ssrn.3932438

Joachim Freyberger

University of Wisconsin - Madison ( email )

716 Langdon Street
Madison, WI 53706-1481
United States

University of Bonn ( email )

Regina-Pacis-Weg 3
Postfach 2220
Bonn, D-53012
Germany

Björn Höppner

University of Bonn - Department of Economics ( email )

Bonn
Germany

Andreas Neuhierl (Contact Author)

Washington University in St. Louis - John M. Olin Business School ( email )

St. Louis, MO
United States

Michael Weber

University of Chicago - Finance ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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