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The Dog That Did Not Bark: A Defense of Return Predictability

  • John H. Cochrane

To question the statistical significance of return predictability, we cannot specify a null that simply turns off that predictability, leaving dividend growth predictability at its essentially zero sample value. If neither returns nor dividend growth are predictable, then the dividend-price ratio is a constant. If the null turns off return predictability, it must turn on the predictability of dividend growth, and then confront the evidence against such predictability in the data. I find that the absence of dividend growth predictability gives much stronger statistical evidence against the null, with roughly 1-2% probability values, than does the presence of return predictability, which only gives about 20% probability values. I argue that tests based on long-run return and dividend growth regressions provide the cleanest and most interpretable evidence on return predictability, again delivering about 1-2% probability values against the hypothesis that returns are unpredictable. I show that Goyal and Welch's (2005) finding of poor out-of-sample R2 does not reject return forecastability. Out-of-sample R2 is poor even if all dividend yield variation comes from time-varying expected returns.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 12026.

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Date of creation: Feb 2006
Date of revision:
Publication status: published as Cochrane, John. "The Dog That Did Not Bark: A Defense of Return Predictability.” Review of Financial Studies 21, 4 (2008): 1533-1575.
Handle: RePEc:nbr:nberwo:12026
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