The multivariate supOU stochastic volatility model

Ole Barndorff-Nielsen and Robert Stelzer ()
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Robert Stelzer: TUM Institute for Advanced Study & Zentrum Mathematik, Technische Universität München, Postal: TUM Institute for Advanced Study & Zentrum Mathematik, Technische Universität München, Boltzmannstraße 3, D-85747 Garching, Germany

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: Using positive semidefinite supOU (superposition of Ornstein-Uhlenbeck type) processes to describe the volatility, we introduce a multivariate stochastic volatility model for financial data which is capable of modelling long range dependence effects. The finiteness of moments and the second order structure of the volatility, the log returns, as well as their “squares” are discussed in detail. Moreover, we give several examples in which long memory effects occur and study how the model as well as the simple Ornstein-Uhlenbeck type stochastic volatility model behave under linear transformations. In particular, the models are shown to be preserved under invertible linear transformations. Finally, we discuss how (sup)OU stochastic volatility models can be combined with a factor modelling approach.

Keywords: factor modelling; Lévy bases; linear transformations; long memory; Ornstein-Uhlenbeck type process; second order moment structure; stochastic volatility (search for similar items in EconPapers)
JEL-codes: C1 C5 G0 G1 (search for similar items in EconPapers)
Pages: 21
Date: 2009-09-17
New Economics Papers: this item is included in nep-ecm and nep-ets
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