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dc.contributor.authorRaknerud, Arvid
dc.contributor.authorSkare, Øivind
dc.date.accessioned2010-11-11T11:37:51Z
dc.date.available2010-11-11T11:37:51Z
dc.date.issued2010
dc.identifier.issn0809-733X
dc.identifier.urihttp://hdl.handle.net/11250/179963
dc.description.abstractThis 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.en_US
dc.description.sponsorshipFinancial support from the Norwegian Research Council ("Finansmarkedsfondet") is gratefully acknowledged.en_US
dc.language.isoengen_US
dc.publisherStatistics Norway, Research Departmenten_US
dc.relation.ispartofseriesDiscussion Papers;614
dc.subjectMultivariate stochastic volatilityen_US
dc.subjectExchange ratesen_US
dc.subjectOrnstein-Uhlenbeck processesen_US
dc.subjectStatistical methodsen_US
dc.subjectStatistical methodologyen_US
dc.subjectEstimationen_US
dc.subjectØkonometrien_US
dc.subjectValutakurseren_US
dc.subjectMultivariat-analyseen_US
dc.subjectSannsynlighetsfordelingen_US
dc.subjectJEL classification: C13en_US
dc.subjectJEL classification: C22en_US
dc.subjectJEL classification: C51en_US
dc.subjectJEL classification: G10en_US
dc.titleMultivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes : a quasi-likelihood approachen_US
dc.typeWorking paperen_US
dc.subject.nsiVDP::Mathematics and natural science: 400::Mathematics: 410en_US
dc.subject.nsiVDP::Social science: 200::Economics: 210en_US
dc.subject.nsiVDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412en_US
dc.source.pagenumber35en_US


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