54 Pages Posted: 15 Mar 2010 Last revised: 6 May 2012
Date Written: August 18, 2011
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.
Keywords: Asset pricing, Model pooling, Model combination, Forecasting, Predictive distributions, Log predictive score
JEL Classification: G12, C52, C53
Suggested Citation: Suggested Citation
O'Doherty, Michael S. and Savin, N. Eugene and Tiwari, Ashish, Modeling the Cross Section of Stock Returns: A Model Pooling Approach (August 18, 2011). Journal of Financial and Quantitative Analysis (JFQA), Forthcoming. Available at SSRN: https://ssrn.com/abstract=1570772 or http://dx.doi.org/10.2139/ssrn.1570772