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The Wishart Autoregressive Process of Multivariate Stochastic Volatility

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  • 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.

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File URL: http://dept.econ.yorku.ca/research/workingPapers/working_papers/2006/War.pdf
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Bibliographic Info

Paper provided by York University, Department of Economics in its series Working Papers with number 2005_2.

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Length: 58 pages
Date of creation: Sep 2005
Date of revision:
Handle: RePEc:yca:wpaper:2005_2

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Keywords: Stochastic Volatility; Car Process; Factor Analysis; Reduced Rank; Realized Volatility;

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