The Wishart Autoregressive process of multivariate stochastic volatility

C. Gourieroux, J. Jasiak, R. Sufana

Research output: Contribution to journalArticlepeer-review

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).

Original languageEnglish
Pages (from-to)167-181
Number of pages15
JournalJournal of Econometrics
Volume150
Issue number2
DOIs
Publication statusPublished - 1 Jun 2009
Externally publishedYes

Keywords

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

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