RFS Advance Access published online on September 22, 2007
Review of Financial Studies, doi:10.1093/rfs/hhm046
The Dog That Did Not Bark: A Defense of Return Predictability
University of Chicago GSB and NBER
Address correspondence to John H. Cochrane, Graduate School of Business, 5807 S. Woodlawn, Chicago IL 60637, 773 702 3059, or e-mail: john.cochrane{at}chicagogsb.edu
JEL: G12, G14, C22
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Abstract |
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If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Long-horizon return forecasts give the same strong evidence. These tests exploit the negative correlation of return forecasts with dividend-yield autocorrelation across samples, together with sensible upper bounds on dividend-yield autocorrelation, to deliver more powerful statistics. I reconcile my findings with the literature that finds poor power in long-horizon return forecasts, and with the literature that notes the poor out-of-sample R2 of return-forecasting regressions.
I acknowledge research support from CRSP and from a NSF grant administered by the NBER. I thank Alan Bester, John Campbell, John Heaton, Lars Hansen, Anil Kashyap, Sydney Ludvigson, Lubos Pastor, Ivo Welch, and an anonymous referee for very helpful comments.