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The Wishart Autoregressive Process of Multivariate Stochastic Volatility

Author

Listed:
  • Joan Jasiak

    (Department of Economics, York University)

  • R. Sufana

    (University of Toronto)

  • C. Gourieroux

    (CREST, CEPREMAP, University of Toronto)

Abstract

The Wishart Autoregressive (WAR) process is a multivariate process of stochastic positive definite matrices. The WAR is proposed in this paper as a dynamic model for stochastic volatility matrices. It yields simple nonlinear forecasts at any horizon and has factor representation, which separates white noise directions from those that contain all information about the past. For illustration, the WAR is applied to a sequence of intraday realized volatility covolatility matrices.

Suggested Citation

  • Joan Jasiak & R. Sufana & C. Gourieroux, 2005. "The Wishart Autoregressive Process of Multivariate Stochastic Volatility," Working Papers 2005_2, York University, Department of Economics.
  • Handle: RePEc:yca:wpaper:2005_2
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    References listed on IDEAS

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    More about this item

    Keywords

    Stochastic Volatility; Car Process; Factor Analysis; Reduced Rank; Realized Volatility;
    All these keywords.

    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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