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Modeling the volatility of the US S&P500 index using an LSTGARCH model

Author

Listed:
  • Gilles Dufrénot

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Vêlayoudom Marimoutou

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Anne Peguin-Feissolle

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper uses the logistic smooth transition GARCH model to study the time-varying volatility of the USSαP 500 index. In the LSTGARCH specification, the parameters are function of some information variables that help capturing the conditional return volatility. Tests of standard GARCH models are provided. Forecast comparisons with the GJR model are proposed, showing an overwhelming predominance of the LSTGARCH model.

Suggested Citation

  • Gilles Dufrénot & Vêlayoudom Marimoutou & Anne Peguin-Feissolle, 2004. "Modeling the volatility of the US S&P500 index using an LSTGARCH model," Post-Print halshs-00390147, HAL.
  • Handle: RePEc:hal:journl:halshs-00390147
    DOI: 10.3917/redp.144.0453
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    References listed on IDEAS

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    1. A. I. McLeod & W. K. Li, 1983. "Diagnostic Checking Arma Time Series Models Using Squared‐Residual Autocorrelations," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 269-273, July.
    2. Peguin-Feissolle, Anne, 1999. "A comparison of the power of some tests for conditional heteroscedasticity," Economics Letters, Elsevier, vol. 63(1), pages 5-17, April.
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