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Contemporaneous-Threshold Smooth Transition GARCH Models

Author

Listed:
  • Michael Dueker
  • Zacharias Psaradakis
  • Martin Sola

    ()

  • Fabio Spagnolo

Abstract

This paper proposes a contemporaneous-threshold smooth transition GARCH (or CSTGARCH) model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization to second conditional moments of the contemporaneous smooth transition threshold autoregressive model of Dueker et al. (2007), in which the regime weights depend on the ex ante probability that a contemporaneous latent regime-specific variable exceeds a threshold value. A key feature of the C-STGARCH model is that its transition function depends on all the parameters of the model as well as on the data. These characteristics allow the model to account for the large persistence and regime shifts that are often observed in the conditional second moments of economic and financial time series.

Suggested Citation

  • Michael Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2009. "Contemporaneous-Threshold Smooth Transition GARCH Models," Department of Economics Working Papers 2009-06, Universidad Torcuato Di Tella.
  • Handle: RePEc:udt:wpecon:2009-06
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    References listed on IDEAS

    as
    1. Markku Lanne & Pentti Saikkonen, 2005. "Non-linear GARCH models for highly persistent volatility," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 251-276, July.
    2. Dueker, Michael J. & Psaradakis, Zacharias & Sola, Martin & Spagnolo, Fabio, 2011. "Multivariate contemporaneous-threshold autoregressive models," Journal of Econometrics, Elsevier, pages 311-325.
    3. Medeiros, Marcelo C. & Veiga, Alvaro, 2009. "Modeling Multiple Regimes In Financial Volatility With A Flexible Coefficient Garch(1,1) Model," Econometric Theory, Cambridge University Press, vol. 25(01), pages 117-161, February.
    4. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    5. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    6. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, pages 517-547.
    7. LUBRANO, Michel, 1998. "Smooth transition GARCH models: a Bayesian perspective," CORE Discussion Papers 1998066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
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    Cited by:

    1. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.

    More about this item

    Keywords

    Conditional heteroskedasticity; Smooth transition GARCH; Threshold; Stock returns.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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