Bayesian analysis of ARMA-GARCH models: A Markov chain sampling approach

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40 Citations (Scopus)


We develop a Markov chain Monte Carlo method for a linear regression model with an ARMA(p, q)-GARCH(r, s) error. To generate a Monte Carlo sample from the joint posterior distribution, we employ a Markov chain sampling with the Metropolis-Hastings algorithm. As illustration, we estimate an ARMA-GARCH model of simulated time series data.

Original languageEnglish
Pages (from-to)57-69
Number of pages13
JournalJournal of Econometrics
Issue number1
Publication statusPublished - 2000 Mar
Externally publishedYes


  • ARMA process
  • Bayesian inference
  • Markov chain Monte Carlo
  • Metropolis-Hastings algorithm

ASJC Scopus subject areas

  • Economics and Econometrics


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