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RFS Advance Access published online on April 2, 2009
Review of Financial Studies, doi:10.1093/rfs/hhp017
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© The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Return Decomposition

Long Chen
Washington University in St. Louis

Xinlei Zhao
Kent State University

Send correspondence to Long Chen, Olin School of Business, Washington University in St. Louis, 212 Simon Hall, 1 Olympian Way, St. Louis, MO 63130-4899; telephone: (314) 935-8374. E-mail: lchen29{at}wustl.edu.

JEL Classification: G11, G12


  Abstract

A crucial issue in asset pricing is to understand the relative importance of discount rate (DR) news and cash flow (CF) news in driving the time-series and cross-sectional variations of stock returns. Many studies directly estimate the DR news but back out the CF news as the residual. We argue that this approach has a serious limitation because the DR news cannot be accurately measured due to the small predictive power, and the CF news, as the residual, inherits the large misspecification error of the DR news. We apply this residual-based decomposition approach to Treasury bonds and equities and find results that are either counterintuitive or unrobust. Potential solutions, including modeling both DR news and CF news directly, the Bayesian model averaging approach, and the principal component analysis, are explored.

We are grateful to an anonymous referee, Ravi Bansal, Jonathan Berk, Geoff Booth, John Campbell, John Cochrane, Murillo Campello, Zhi Da, Robert Dittmar, Hui Guo, Joel Hasbrouck (the editor), John Heaton, Dana Kiku, Raymond Kan, Martin Lettau, Sydney Ludvigson, Pedro Santa-Clara, Clemens Sialm, Robert Stambaugh, Annette Vissing-Jorgensen, Tuomo Vuolteenaho, Jessica Wachter, Chao Wei, Motohiro Yogo, Kathy Yuan, Lu Zhang and seminar participants at 2006 NBER asset pricing meeting, 2006 FEA annual meeting, 2007 AFA annual meeting, University of Binghamton, University of Michigan, and Michigan State University for their very helpful comments. We thank the following authors for kindly providing data: Kenneth French, Amit Goyal, Sydney Ludvigson, Robert Shiller, Tuomo Vuolteenaho, Ivo Welch, and Lu Zhang. We are responsible for all remaining errors.


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