Modeling the Cross Section of Stock Returns: A Model Pooling Approach
Michael S. O'Doherty
University of Missouri at Columbia - Department of Finance
N. Eugene Savin
University of Iowa - Henry B. Tippie College of Business - Department of Economics
University of Iowa
August 18, 2011
Journal of Financial and Quantitative Analysis (JFQA), Forthcoming
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.
Number of Pages in PDF File: 54
Keywords: Asset pricing, Model pooling, Model combination, Forecasting, Predictive distributions, Log predictive score
JEL Classification: G12, C52, C53
Date posted: March 15, 2010 ; Last revised: May 6, 2012
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