Marginal likelihood for Markov-switching and change-point GARCH models

GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks in the volatility process. Flexible alternatives are Markov-switching GARCH and change-point GARCH models. They require estimation by MCMC methods due to the path dependence problem. An unsolved issu...

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Veröffentlicht in:	Journal of econometrics 2014-01, Vol.178 (3), p.508-522
Hauptverfasser:	Bauwens, Luc, Dufays, Arnaud, Rombouts, Jeroen V.K.
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian inference Change-point model Chaos theory Econometric models Estimation GARCH GARCH models Linear models Marginal likelihood Markov analysis Markov-switching model Markovian processes Mathematical problems Maximum likelihood method Model testing Monte Carlo simulation Particle MCMC Simulation Stochastic models Stochastic processes Studies Time series Volatility
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