Why Long Horizons? A Study of Power Against Persistent Alternatives
John Campbell ()
Scholarly Articles from Harvard University Department of Economics
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. Monte 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.
References: Add references at CitEc
Citations: View citations in EconPapers (42) Track citations by RSS feed
Published in Journal of Empirical Finance
Downloads: (external link)
Journal Article: Why long horizons? A study of power against persistent alternatives (2001)
Working Paper: Why Long Horizons: A Study of Power Against Persistent Alternatives (1993)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:hrv:faseco:3196341
Access Statistics for this paper
More papers in Scholarly Articles from Harvard University Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Office for Scholarly Communication ().