TY - JOUR
T1 - Testing for mean reversion in heteroskedastic data II
T2 - Autoregression tests based on Gibbs-sampling-augmented randomization
AU - Kim, Chang Jin
AU - Nelson, Charles R.
N1 - Funding Information:
Kim greatly appreciates support from the department. Nelson acknowledges support from the Van Voorhis endowment at the University of Washington and from the National Science Foundation.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 1998/10
Y1 - 1998/10
N2 - 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.
AB - 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.
KW - Autoregression tests
KW - C15
KW - C22
KW - G12
KW - Gibbs sampling
KW - Mean aversion
KW - Mean reversion
KW - Randomization
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U2 - 10.1016/S0927-5398(98)00006-1
DO - 10.1016/S0927-5398(98)00006-1
M3 - Article
AN - SCOPUS:0039492711
SN - 0927-5398
VL - 5
SP - 385
EP - 396
JO - Journal of Empirical Finance
JF - Journal of Empirical Finance
IS - 4
ER -