Theory and inference for a Markov switching GARCH model
AbstractWe 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 existence 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 S&P500 daily returns. Copyright The Author(s). Journal compilation Royal Economic Society 2010.
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Bibliographic InfoArticle provided by Royal Economic Society in its journal Econometrics Journal.
Volume (Year): 13 (2010)
Issue (Month): 2 (07)
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Other versions of this item:
- Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2007. "Theory and inference for a Markov switching Garch model," Cahiers de recherche 07-09, HEC Montréal, Institut d'économie appliquée.
- Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2007. "Theory and Inference for a Markov-Switching GARCH Model," Cahiers de recherche 0733, CIRPEE.
- BAUWENS, Luc & PREMINGER, Arie & ROMBOUTS, Jeroen V.K., 2007. "Theory and inference for a Markov switching GARCH model," CORE Discussion Papers 2007055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc, BAUWENS & Arie, PREMINGER & Jeroen, ROMBOUTS, 2007. "Theory and inference for a Markov switching GARCH model," Discussion Papers (ECON - DÃ©partement des Sciences Economiques) 2007033, Université catholique de Louvain, Département des Sciences Economiques.
- BAUWENS, Luc & PREMINGER, Arie & ROMBOUTS, Jeroen VK, . "Theory and inference for a Markov switching Garch model," CORE Discussion Papers RP -2303, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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