Most 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.

block structures, curse of dimensionality, multivariate stochastic volatility
Econometric and Statistical Methods: General (jel C10), Time-Series Models; Dynamic Quantile Regressions (jel C32), Model Construction and Estimation (jel C51)
Erasmus School of Economics
Econometric Institute Research Papers
Report / Econometric Institute, Erasmus University Rotterdam
Erasmus School of Economics

Asai, M, & Caporin, M. (2009). Block Structure Multivariate Stochastic Volatility Models (No. EI 2009-51). Report / Econometric Institute, Erasmus University Rotterdam (pp. 1–34). Erasmus School of Economics. Retrieved from