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

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References

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