Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/37511
Year of Publication: 
2010
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie - Session: Advances in Time Series Analysis No. B6-V2
Publisher: 
Verein für Socialpolitik, Frankfurt a. M.
Abstract: 
We generalize the basic Wishart multivariate stochastic volatility model of Philipov and Glickmann (2006) to encompass regime switching behavior. The latent state variable is driven by a first-order Markov process. In order to estimate the proposed model we use Bayesian Markov Chain Monte Carlo procedures. For the computation of filtered estimates of the latent variances and covariances we rely upon particle filter techniques. The model is applied to five European stock index returns. Our results show that our proposed regime-switching specification substantially improves the estimates of the conditional covariance matrix and the VaR performance relative to the basic model.
Subjects: 
Markov Switching , MCMC
Multivariate Stochastic Volatility
Particle Filter
Volatility Spillovers
JEL: 
C11
C15
C32
Document Type: 
Conference Paper

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