Efficient Gibbs Sampling for Markov Switching GARCH Models

40 Pages Posted: 11 Jan 2013

See all articles by Monica Billio

Monica Billio

Ca Foscari University of Venice - Dipartimento di Economia

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics

Ayokunle Anthony Osuntuyi

Ca Foscari University of Venice

Date Written: December 1, 2012

Abstract

We develop efficient simulation techniques for Bayesian inference on switching GARCH models. Our contribution to existing literature is manifold. First, we discuss different multi-move sampling techniques for Markov Switching (MS) state space models with particular attention to MS-GARCH models. Our multi-move sampling strategy is based on the Forward Filtering Backward Sampling (FFBS) applied to an approximation of MS-GARCH. Another important contribution is the use of multi-point samplers, such as the Multiple-Try Metropolis (MTM) and the Multiple Trial Metropolize Independent Sampler, in combination with FFBS for the MS-GARCH process. In this sense we extend to the MS state space models the work of So (2006) on efficient MTM sampler for continuous state space models. Finally, we suggest to further improve the sampler efficiency by introducing the antithetic sampling of Craiu and Meng (2005) and Craiu and Lemieux (2007) within the FFBS. Our simulation experiments on MS-GARCH model show that our multi-point and multi-move strategies allow the sampler to gain efficiency when compared with single-move Gibbs sampling.

Keywords: Bayesian inference, GARCH, Markov switching, Multiple-Try Metropolis

JEL Classification: C11, C15, C53, G17

Suggested Citation

Billio, Monica and Casarin, Roberto and Osuntuyi, Ayokunle Anthony, Efficient Gibbs Sampling for Markov Switching GARCH Models (December 1, 2012). Available at SSRN: https://ssrn.com/abstract=2198837 or http://dx.doi.org/10.2139/ssrn.2198837

Monica Billio

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

HOME PAGE: http://www.unive.it/persone/billio

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics ( email )

San Giobbe 873/b
Venice, 30121
Italy
+39 030.298.91.49 (Phone)
+39 030.298.88.37 (Fax)

HOME PAGE: http://sites.google.com/view/robertocasarin

Ayokunle Anthony Osuntuyi (Contact Author)

Ca Foscari University of Venice ( email )

Dorsoduro 3246
Venice, Veneto 30123
Italy

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
68
Abstract Views
703
rank
404,934
PlumX Metrics