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A Bayesian algorithm for a Markov Switching GARCH model


  • Dhiman Das


Applications of GARCH methods are now quite widespread in macroeconomic and financial time series. New formulations have been developed in order to address the statistical regularity observed in these time series such as assymetric nature and strong persistence of variances. This paper develops a ARMA-GARCH model with Markov switching conditional variances to simulataneously address the above two conditions. A Bayesian algorithm is developed for the estimation purpose and applied to two datasets

Suggested Citation

  • Dhiman Das, 2004. "A Bayesian algorithm for a Markov Switching GARCH model," Computing in Economics and Finance 2004 30, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:30

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    References listed on IDEAS

    1. Jan Fagerberg, 2003. "Schumpeter and the revival of evolutionary economics: an appraisal of the literature," Journal of Evolutionary Economics, Springer, vol. 13(2), pages 125-159, April.
    2. Mueller, Dennis C, 1976. "Public Choice: A Survey," Journal of Economic Literature, American Economic Association, vol. 14(2), pages 395-433, June.
    3. Richard R. Nelson, 1995. "Recent Evolutionary Theorizing about Economic Change," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 48-90, March.
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    Cited by:

    1. Luc Bauwens & Arie Preminger & Jeroen V. K. Rombouts, 2010. "Theory and inference for a Markov switching GARCH model," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 218-244, July.

    More about this item


    GARCH Markov Switching Bayesian;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation


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