Testing for Mean Reversion in Heteroskedastic Data II: Autoregression Tests Based on Gibbs-Sampling-Augmented Randomization

Chang-Jin Kim () and Charles Nelson

Working Papers from University of Washington, Department of Economics

Abstract: A decade ago Fama and French (1998) estimated that 40% variations in stock returns was predictable over horizons of 3-5 years, which they attributed to a mean reverting stationary component in prices. While it has been clear that the Depression and war years exert a strong influence on these estimates, it has not been clear whether the large returns of that period contribute to the information in the data or rather are a source of noise to be discounted in estimation. This paper uses the Gibbs-sampling-augmented randomization methodology to address the problem of heteroskedasticity in estimation of multi-period return autoregressions.

Keywords: STATISTICS (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 11 pages
Date: 1997
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Working Paper: Testing for Mean Reversion in Heteroskedastic Data II: Autoregression Tests Based on Gibbs-Sampling-Augmented Randomization (1997)
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