Gribisch, Bastian (2016). Multivariate Wishart stochastic volatility and changes in regime. AStA-Adv. Stat. Anal., 100 (4). S. 443 - 474. NEW YORK: SPRINGER. ISSN 1863-818X

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Abstract

This paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Glickman (J Bus Econ Stat 24:313-328, 2006) and Asai and McAleer (J Econom 150:182-192, 2009) to encompass regime-switching behavior. The latent state variable is driven by a first-order Markov process. The model allows for state-dependent (co)variance and correlation levels and state-dependent volatility spillover effects. Parameter estimates are obtained using Bayesian Markov Chain Monte Carlo procedures and filtered estimates of the latent variances and covariances are generated by particle filter techniques. The model is applied to five European stock index return series. The results show that the proposed regime-switching specification substantially improves the fit to persistent covariance dynamics relative to the basic model.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Gribisch, BastianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-260724
DOI: 10.1007/s10182-016-0269-9
Journal or Publication Title: AStA-Adv. Stat. Anal.
Volume: 100
Number: 4
Page Range: S. 443 - 474
Date: 2016
Publisher: SPRINGER
Place of Publication: NEW YORK
ISSN: 1863-818X
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY; MARGINAL LIKELIHOOD; GENERALIZED ARCH; MODELS; SPILLOVERS; CONTAGION; VARIANCE; INTERDEPENDENCE; DISTRIBUTIONS; INFERENCEMultiple languages
Statistics & ProbabilityMultiple languages
Refereed: Yes
URI: http://kups.ub.uni-koeln.de/id/eprint/26072

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