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Why Long Horizons: A Study of Power Against Persistent Alternatives

  • John Y. Campbell

This paper studies tests of predictability in regressions with a given AR(1) regressor and an asset return dependent variable measured over a short or long horizon. The paper shows that when there is a persistent predictable component in the return, an increase in the horizon may increase the R2 statistic of the regression and the approximate slope of a predictability test. Mone Carlo experiments show that long-horizon regression tests have serious size distortions when asymptotic critical values are used, but some versions of such tests have power advantages remaining after size is corrected.

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File URL: http://www.nber.org/papers/t0142.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0142.

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Date of creation: Sep 1993
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Publication status: published as Campbell, John Y. "Why Long Horizons? A Study Of Power Against Persistent Alternatives," Journal of Empirical Finance, 2001, v8(5,Dec), 459-491.
Handle: RePEc:nbr:nberte:0142
Note: AP
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  35. Campbell, John, 1991. "A Variance Decomposition for Stock Returns," Scholarly Articles 3207695, Harvard University Department of Economics.
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  39. Jegadeesh, Narasimhan, 1991. " Seasonality in Stock Price Mean Reversion: Evidence from the U.S. and the U.K," Journal of Finance, American Finance Association, vol. 46(4), pages 1427-44, September.
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