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

Posted: 8 Aug 2008

See all articles by John Y. Campbell

John Y. Campbell

Harvard University - Department of Economics; National Bureau of Economic Research (NBER)

Samuel Brodsky Thompson

Arrowstreet Capital, L.P.

Date Written: July 2008

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.

Keywords: G10, G11

Suggested Citation

Campbell, John Y. and Thompson, Samuel Brodsky, Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? (July 2008). The Review of Financial Studies, Vol. 21, Issue 4, pp. 1509-1531, 2008. Available at SSRN: https://ssrn.com/abstract=1212066 or http://dx.doi.org/hhm055

John Y. Campbell (Contact Author)

Harvard University - Department of Economics ( email )

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HOME PAGE: http://scholar.harvard.edu/campbell

National Bureau of Economic Research (NBER)

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Samuel Brodsky Thompson

Arrowstreet Capital, L.P. ( email )

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Cambridge, MA 02138
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