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The Wishart Autoregressive process of multivariate stochastic volatility

Author

Listed:
  • 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).

Suggested Citation

  • Gourieroux, C. & Jasiak, J. & Sufana, R., 2009. "The Wishart Autoregressive process of multivariate stochastic volatility," Journal of Econometrics, Elsevier, vol. 150(2), pages 167-181, June.
  • Handle: RePEc:eee:econom:v:150:y:2009:i:2:p:167-181
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    More about this item

    Keywords

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

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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