Discussion Papers no. 614

A quasi-likelihood approach

Multivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes

This paper extends the ordinary quasi-likelihood estimator for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck (OU) processes to vector processes. Despite the fact that multivariate modeling of asset returns is essential for portfolio optimization and risk management -- major areas of financial analysis -- the literature on multivariate modeling of asset prices in continuous time is sparse, both with regard to theoretical and applied results. This paper uses non-Gaussian OU-processes as building blocks for multivariate models for high frequency financial data. The OU framework allows exact discrete time transition equations that can be represented on a linear state space form. We show that a computationally feasible quasi-likelihood function can be constructed by means of the Kalman filter also in the case of high-dimensional vector processes. The framework is applied to Euro/NOK and US Dollar/NOK exchange rate data for the period 2.1.1989-4.2.2010

Om publikasjonen

Tittel

Multivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes. A quasi-likelihood approach

Ansvarlige

Arvid Raknerud, Øivind Skare

Serie og -nummer

Discussion Papers no. 614

Utgiver

Statistics Norway, Research Department

Emne

Discussion Papers

Antall sider

35

Målform

Engelsk

Om Discussion Papers

Discussion papers comprise research papers intended for international journals and books. A preprint of a Discussion Paper may be longer and more elaborate than a standard journal article as it may include intermediate calculations, background material etc.

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