Regime switching GARCH models

Luc Bauwens, Arie Preminger and Jeroen Rombouts

No 06-08, Cahiers de recherche from HEC Montréal, Institut d'économie appliquée

Abstract: We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past information. We provide sufficient conditions for stationarity and existence of moments. Because of path dependence, maximum likelihood estimation is infeasible. By enlarging the parameter space to include the state variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We apply this model using the NASDAQ daily return series.

Keywords: GARCH; regime switching; Bayesian inference. (search for similar items in EconPapers)
JEL-codes: C11 C22 C52 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2006-06
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

Downloads: (external link)
http://www.hec.ca/iea/cahiers/2006/iea0608_jrombouts.pdf (application/pdf)

Related works:
Working Paper: Regime switching GARCH models (2006)
Working Paper: Regime switching GARCH models (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:iea:carech:0608

Ordering information: This working paper can be ordered from
Institut d'économie appliquée HEC Montréal 3000, Chemin de la Côte-Sainte-Catherine Montréal, Québec H3T 2A7

The price is Free.

Access Statistics for this paper

More papers in Cahiers de recherche from HEC Montréal, Institut d'économie appliquée Institut d'économie appliquée HEC Montréal 3000, Chemin de la Côte-Sainte-Catherine Montréal, Québec H3T 2A7. Contact information at EDIRC.
Bibliographic data for series maintained by Patricia Power ().