The Wishart Autoregressive process of multivariate stochastic volatility

C. Gourieroux, J. Jasiak and R. Sufana

Journal of Econometrics, 2009, vol. 150, issue 2, pages 167-181

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).

Keywords: Stochastic; volatility; Car; process; Autoregressive; gamma; process; Factor; analysis; Reduced; rank; Realized; volatility (search for similar items in EconPapers)
Date: 2009
View citations in EconPapers

Downloads: (external link)
http://www.sciencedirect.com/science/article/B6VC0 ... 7d550f97dade8e18a351
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:eee:econom:v:150:y:2009:i:2:p:167-181

Access Statistics for this article

Journal of Econometrics is edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao, P. M. Robinson and A. Zellner

More articles in Journal of Econometrics from Elsevier
Series data maintained by Heidi Boesdal ().