Journal of Financial and Quantitative Analysis

Research Articles

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

Michael O’Dohertya1, N. E. Savina2 and Ashish Tiwaria2

a1 odohertym@missouri.edu, Trulaske College of Business, University of Missouri,513 Cornell Hall, Columbia, MO 65211

a2 gene-savin@uiowa.edu, ashish-tiwari@uiowa.edu, Tippie College of Business, University of Iowa, 108 PBB, Iowa City, IA 52242

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.

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