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The Wishart Autoregressive process of multivariate stochastic volatility

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Author Info
Gourieroux, C.
Jasiak, J.
Sufana, R.
Abstract

The Wishart Autoregressive (WAR) process is a dynamic model for time series of multivariate stochastic volatility. The WAR naturally accommodates the positivity and symmetry of volatility matrices and provides closed-form non-linear forecasts. The estimation of the WAR is straighforward, as it relies on standard methods such as the Method of Moments and Maximum Likelihood. For illustration, the WAR is applied to a sequence of intraday realized volatility-covolatility matrices from the Toronto Stock Market (TSX).

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Publisher Info
Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 150 (2009)
Issue (Month): 2 (June)
Pages: 167-181
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Handle: RePEc:eee:econom:v:150:y:2009:i:2:p:167-181

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Web page: http://www.elsevier.com/locate/jeconom

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Related research
Keywords: Stochastic volatility Car process Autoregressive gamma process Factor analysis Reduced rank Realized volatility;

Cited by:
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  1. Almut E. D. Veraart & Luitgard A. M. Veraart, 2009. "Stochastic volatility and stochastic leverage," CREATES Research Papers 2009-20, School of Economics and Management, University of Aarhus. [Downloadable!]
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This page was last updated on 2009-12-9.

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