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Modeling the Cross Section of Stock Returns: A Model Pooling Approach

Published online by Cambridge University Press:  04 October 2012

Michael O’Doherty ,
N. E. Savin  and
Ashish Tiwari
Michael O’Doherty
Affiliation:
odohertym@missouri.edu, Trulaske College of Business, University of Missouri,513 Cornell Hall, Columbia, MO 65211
N. E. Savin
Affiliation:
gene-savin@uiowa.edu, ashish-tiwari@uiowa.edu, Tippie College of Business, University of Iowa, 108 PBB, Iowa City, IA 52242
Ashish Tiwari
Affiliation:
gene-savin@uiowa.edu, ashish-tiwari@uiowa.edu, Tippie College of Business, University of Iowa, 108 PBB, Iowa City, IA 52242
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Abstract

Model selection (i.e., the choice of an asset pricing model to the exclusion of competing models) is an inherently misguided strategy when the true model is unavailable to the researcher. This paper illustrates the advantages of a model pooling approach in characterizing the cross section of stock returns. The optimal pool combines models using the log predictive score criterion, a measure of the out-of-sample performance of each model, and consistently outperforms the best individual model. The benefits to model pooling are most pronounced during periods of economic stress, and it is a valuable tool for asset allocation decisions.

Type
Research Articles
Information
Journal of Financial and Quantitative Analysis , Volume 47 , Issue 6 , December 2012 , pp. 1331 - 1360
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2012

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