Bayesian Estimation of a Markov-Switching Threshold Asymmetric GARCH Model with Student-Tinnovations

22 Pages Posted: 27 Apr 2009

See all articles by David Ardia

David Ardia

HEC Montreal - Department of Decision Sciences

Date Written: 2008-07

Abstract

A Bayesian estimation of a regime-switching threshold asymmetric GARCH model is proposed. The specification is based on a Markov-switching model with Student-tinnovations and Kseparate GJR(1,1) processes whose asymmetries are located at free non-positive threshold parameters. The model aims at determining whether or not: (i) structural breaks are present within the volatility dynamics; (ii) asymmetries (leverage effects) are present, and are different between regimes and (iii) the threshold parameters (locations of bad news) are similar between regimes. A novel MCMC scheme is proposed which allows for a fully automatic Bayesian estimation of the model. The presence of two distinct volatility regimes is shown in an empirical application to the Swiss Market Index log-returns. The posterior results indicate no differences with regards to the asymmetries and their thresholds when comparing highly volatile periods with the milder ones. Comparisons with a single-regime specification indicates a better in-sample fit and a better forecasting performance for the Markov-switching model.

Suggested Citation

Ardia, David, Bayesian Estimation of a Markov-Switching Threshold Asymmetric GARCH Model with Student-Tinnovations (2008-07). Econometrics Journal, Vol. 12, Issue 1, pp. 105-126, March 2009, Available at SSRN: https://ssrn.com/abstract=1376053 or http://dx.doi.org/10.1111/j.1368-423X.2008.00253.x

David Ardia (Contact Author)

HEC Montreal - Department of Decision Sciences ( email )

3000 Côte-Sainte-Catherine Road
Montreal, QC H2S1L4
Canada

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