Block Structure Multivariate Stochastic Volatility Models
AbstractMost multivariate variance models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with milder restrictions, whose purpose was to combine the need for interpretability and efficiency faced by model users with the computational problems that may emerge when the number of assets is quite large. We contribute to this strand of the literature proposing a block-type parameterization for multivariate stochastic volatility models.
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Bibliographic InfoPaper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 10/24.
Length: 31 pages
Date of creation: 01 May 2010
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Block structures; multivariate stochastic volatility; curse of dimensionality;
Other versions of this item:
- Manabu Asai & Massimiliano Caporin & Michael McAleer, 2009. "Block Structure Multivariate Stochastic Volatility Models," CIRJE F-Series CIRJE-F-699, CIRJE, Faculty of Economics, University of Tokyo.
- Asai, M. & Caporin, M., 2009. "Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2009-51, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-05-29 (All new papers)
- NEP-ECM-2010-05-29 (Econometrics)
- NEP-ETS-2010-05-29 (Econometric Time Series)
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