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Measuring the Predictable Variation in Stock and Bond Returns

Chris Kirby

Rice University

Review of Financial Studies 1997

Recent studies show that when a regression model is used to forecast stock and bond returns, the sample R^2 increases dramatically with the length of the return horizon. These studies argue, therefore, that long-horizon returns are highly predictable. This article presents evidence that suggests otherwise. Long-horizon regressions can easily yield large values of the sample R^2, even if the populations R^2 is smaller or zero. Moreover, long-horizon regressions with a small or zero population R^2 can produce t-ratios that might be interpreted as evidence of strong predictability. In general, the analysis provides little support for the view that long-horizon returns are highly predictable.

DOI
10.1093/rfs/10.3.579
Volume
10 (3)
Pages
579-630
Language
en
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BibTeX
Sources
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