The multivariate supOU stochastic volatility model
AbstractUsing 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.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2009-42.
Date of creation: 17 Sep 2009
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Web page: http://www.econ.au.dk/afn/
factor modelling; Lévy bases; linear transformations; long memory; Ornstein-Uhlenbeck type process; second order moment structure; stochastic volatility;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- G0 - Financial Economics - - General
- G1 - Financial Economics - - General Financial Markets
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-10-10 (All new papers)
- NEP-ECM-2009-10-10 (Econometrics)
- NEP-ETS-2009-10-10 (Econometric Time Series)
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- Richard B. Olsen & Ulrich A. Müller & Michel M. Dacorogna & Olivier V. Pictet & Rakhal R. Davé & Dominique M. Guillaume, 1997. "From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (*)," Finance and Stochastics, Springer, vol. 1(2), pages 95-129.
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