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Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?

Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? Goyal and Welch (2007) argue that the historical average excess stock return forecasts future excess stock returns better than regressions of excess returns on predictor variables. In this article, we show that many predictive regressions beat the historical average return, once weak restrictions are imposed on the signs of coefficients and return forecasts. The out-of-sample explanatory power is small, but nonetheless is economically meaningful for mean-variance investors. Even better results can be obtained by imposing the restrictions of steady-state valuation models, thereby removing the need to estimate the average from a short sample of volatile stock returns. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Review of Financial Studies Oxford University Press

Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?

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References (50)

Publisher
Oxford University Press
Copyright
© The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Subject
Articles
ISSN
0893-9454
eISSN
1465-7368
DOI
10.1093/rfs/hhm055
Publisher site
See Article on Publisher Site

Abstract

Goyal and Welch (2007) argue that the historical average excess stock return forecasts future excess stock returns better than regressions of excess returns on predictor variables. In this article, we show that many predictive regressions beat the historical average return, once weak restrictions are imposed on the signs of coefficients and return forecasts. The out-of-sample explanatory power is small, but nonetheless is economically meaningful for mean-variance investors. Even better results can be obtained by imposing the restrictions of steady-state valuation models, thereby removing the need to estimate the average from a short sample of volatile stock returns.

Journal

The Review of Financial StudiesOxford University Press

Published: Jul 20, 2008

Keywords: JEL Classification G10 G11

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