J. Japan Statist. Soc., Vol. 36 (No. 2), pp. 199-212, 2006

Comparison of MCMC Methods for Estimating GARCH Models

Manabu Asai

Abstract. This paper reviews several MCMC methods for estimating the class of ARCH models, and compare performances of them. With respect to the mixing, efficiency and computational requirement of the MCMC, this paper found the best method is the tailored approach based on the acceptance-rejection Metropolis-Hastings algorithm.

Key words and phrases: Bayesian inference, GARCH, Gibbs sampler, Markov chain Monte Carlo, Metropolis-Hastings algorithm.

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