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Variations in returns/volatility and persistence in variance. An application to the Spanish stock market

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  • Laura Mun Oz
  • Pilar Olave
  • Manuel Salvador

Abstract

A methodology is proposed to select the information set in ARMA-GARCH models in order to forecast the future evolution of an univariate heteroscedastic time series when it is suspected that the DGP is time changing. Using this methodology the stability of the DGP in the Spanish Stock Market is analysed. In this case it is shown that the DGP is time-varying and, in particular, the persistence in variance is over-valued using classical methods. Furthermore, the predictive intervals obtained have better coverage properties, by more adequately reflecting the uncertainty associated to the evolution of the time series being analysed.

Suggested Citation

  • Laura Mun Oz & Pilar Olave & Manuel Salvador, 2002. "Variations in returns/volatility and persistence in variance. An application to the Spanish stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 9(13), pages 899-905.
    • Handle: RePEc:taf:apeclt:v:9:y:2002:i:13:p:899-905
    DOI: 10.1080/13504850210165847
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    References listed on IDEAS

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    1. Baillie, Richard T. & Bollerslev, Tim, 1992. "Prediction in dynamic models with time-dependent conditional variances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 91-113.
    2. 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.
    3. Phillips, Peter C B, 1996. "Econometric Model Determination," Econometrica, Econometric Society, vol. 64(4), pages 763-812, July.
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