Modeling the Cross Section of Stock Returns: A Model Pooling Approach
54 Pages Posted: 15 Mar 2010 Last revised: 6 May 2012
Date Written: August 18, 2011
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.
Keywords: Asset pricing, Model pooling, Model combination, Forecasting, Predictive distributions, Log predictive score
JEL Classification: G12, C52, C53
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
Consumption, Aggregate Wealth and Expected Stock Returns
By Martin Lettau and Sydney C. Ludvigson
-
Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles
By Ravi Bansal and Amir Yaron
-
Dividend Yields and Expected Stock Returns: Alternative Procedures for Interference and Measurement
-
Resurrecting the (C)Capm: A Cross-Sectional Test When Risk Premia are Time-Varying
By Martin Lettau and Sydney C. Ludvigson
-
Stock Return Predictability: Is it There?
By Geert Bekaert and Andrew Ang
-
Stock Return Predictability: Is it There?
By Geert Bekaert and Andrew Ang
-
Resurrecting the (C)Capm: A Cross-Sectional Test When Risk Premia Wre Time-Varying
By Martin Lettau and Sydney C. Ludvigson