Testing for mean reversion in heteroskedastic data II

Autoregression tests based on Gibbs-sampling-augmented randomization

Chang-Jin Kim, Charles R. Nelson

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

A decade ago Fama and French [Fama, E.G., French, K.R., 1988. Permanent and temporary components of stock prices. J. Political Econ. 96 (2) 246-273] estimated that 40% of variation in stock returns was predictable over horizons of 3-5 yr, 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. Extending the sample period to 1995, we find little evidence of mean reversion. Examining subsamples, only 1926-1946 provides any evidence of mean reversion, while the post war period is characterized by mean aversion. A test of structural change suggests that this difference between pre and post war periods is significant.

Original languageEnglish
Pages (from-to)385-396
Number of pages12
JournalJournal of Empirical Finance
Volume5
Issue number4
Publication statusPublished - 1998 Oct 1

Fingerprint

Testing
Mean reversion
Randomization
Gibbs sampling
Autoregression
Mean-reverting
Structural change
Stock prices
Stock returns
Heteroskedasticity
Methodology

Keywords

  • Autoregression tests
  • C15
  • C22
  • G12
  • Gibbs sampling
  • Mean aversion
  • Mean reversion
  • Randomization

ASJC Scopus subject areas

  • Economics and Econometrics
  • Finance

Cite this

Testing for mean reversion in heteroskedastic data II : Autoregression tests based on Gibbs-sampling-augmented randomization. / Kim, Chang-Jin; Nelson, Charles R.

In: Journal of Empirical Finance, Vol. 5, No. 4, 01.10.1998, p. 385-396.

Research output: Contribution to journalArticle

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