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A Bayesian Analysis of Autoregressive Models with Exogenous Variables and Power-Transformed and Threshold GARCH Errors

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  • Qiang Xia
  • Rubing Liang
  • Jinshan Liu

Abstract

Consider a class of autoregressive models with exogenous variables and power transformed and threshold GARCH (ARX-PTTGARCH) errors, which is a natural generalization of the standard and special GARCH model. We propose a Bayesian method to show that combining Gibbs sampler and Metropolis-Hastings algorithm to give a Bayesian analysis can be applied to estimate parameters of ARX-PTTGARCH models with success.

Suggested Citation

  • Qiang Xia & Rubing Liang & Jinshan Liu, 2015. "A Bayesian Analysis of Autoregressive Models with Exogenous Variables and Power-Transformed and Threshold GARCH Errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(9), pages 1967-1980, May.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:9:p:1967-1980
    DOI: 10.1080/03610926.2013.863926
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