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A Bayesian algorithm for a Markov Switching GARCH model

Author

Listed:
  • Dhiman Das
Abstract
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
    as

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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

    Keywords

    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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