The Wishart Autoregressive process of multivariate stochastic volatility

Christian Gourieroux, Joann Jasiak and R. Sufana

Journal of Econometrics, 2009, vol. 150, issue 2, 167-181

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).

Keywords: Stochastic; volatility; Car; process; Autoregressive; gamma; process; Factor; analysis; Reduced; rank; Realized; volatility (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (144)

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Working Paper: The Wishart Autoregressive Process of Multivariate Stochastic Volatility (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:150:y:2009:i:2:p:167-181

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