Theory and inference for a Markov switching GARCH model

Luc Bauwens, Preminger Arie and Jeroen Rombouts
Additional contact information
Preminger Arie: University of Haifa, Israel, Department of Economics

No 2007033, Discussion Papers (ECON - Département des Sciences Economiques) from Université catholique de Louvain, Département des Sciences Economiques

Abstract: We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric ergodicity and existene of moments of the process. Because of path dependence, maximum likelihood estimation is not feasible. By enlarging the parameter space to include the state variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We illustrate the model on SP500 daily returns.

Keywords: GARCH; Markov-switching; Bayesian inference (search for similar items in EconPapers)
JEL-codes: C11 C22 C52 (search for similar items in EconPapers)
Pages: 28
Date: 2007-09-01
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (8)

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Related works:
Journal Article: Theory and inference for a Markov switching GARCH model (2010)
Working Paper: Theory and inference for a Markov switching Garch model (2010)
Working Paper: Theory and inference for a Markov switching GARCH model (2007)
Working Paper: Theory and inference for a Markov switching Garch model (2007)
Working Paper: Theory and Inference for a Markov-Switching GARCH Model (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:ctl:louvec:2007033

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