Arbeitspapier

Multivariate wishart stochastic volatility and changes in regime

This paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Glickman (2006) and Asai and McAleer (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 in-sample fit and the VaR forecasting performance relative to the basic model.

Sprache
Englisch

Erschienen in
Series: Economics Working Paper ; No. 2012-14

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Financial Econometrics
Financial Forecasting and Simulation
Thema
Multivariate stochastic volatility
Dynamic correlations
Wishart distribution
Markov switching
Markov chain Monte Carlo

Ereignis
Geistige Schöpfung
(wer)
Gribisch, Bastian
Ereignis
Veröffentlichung
(wer)
Kiel University, Department of Economics
(wo)
Kiel
(wann)
2012

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Gribisch, Bastian
  • Kiel University, Department of Economics

Entstanden

  • 2012

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