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Persistence in Variance, Structural Change, and the GARCH Model

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  • Lamoureux, Christopher G
  • Lastrapes, William D

Abstract

This article examines the persistence of the variance, as measured by the generalized autoregressive conditional heteroskedasticity (GARCH) model, in stock-return data. In particular, we investigate the extent to which persistence in variance may be overstated because of the existence of, and failure to take account of, deterministic structural shifts in the model. Both an analysis of daily stock-return data and a Monte Carlo simulation experiment confirm the hypothesis that GARCH measures of persistence in variance are sensitive to this type of model misspecification.

Suggested Citation

  • Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
  • Handle: RePEc:bes:jnlbes:v:8:y:1990:i:2:p:225-34
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    1. Zvi Griliches, 1984. "Data Problems in Econometrics," NBER Technical Working Papers 0039, National Bureau of Economic Research, Inc.
    2. Zvi Griliches, 1998. "Interindustry Technology Flows and Productivity Growth: A Reexamination," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 241-250 National Bureau of Economic Research, Inc.
    3. George J. Stigler & James K. Kindahl, 1970. "The Behavior of Industrial Prices," NBER Books, National Bureau of Economic Research, Inc, number stig70-1, January.
    4. Lichtenberg, Frank R., 1986. "Energy prices and induced innovation," Research Policy, Elsevier, vol. 15(2), pages 67-75, April.
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