of computational burden and estimation error. First the number of correlation coefficients to be estimated would grow … volatilities of stocks and implied volatility of the basket. To analyze this structure and the dynamics of the ICS we employ a …

series with a zero spectral density at some frequency. Estimation and inference can be performed using an Instrumental … an analysis of the comovement between Germany, Austria and the United Kingdom is presented. -- common feature analysis …

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …

and the short-run or transitory components of the volatility of daily stock market returns using bivariate mixture models …. For this purpose, the Standard bivariate mixture model of Tauchen and Pitts (1983) in which volatility and volume are … each endowed with their own dynamic behavior are allowed to direct volatility and volume. Since the latent information …

forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

This paper proposes structured parametrizations for multivariate volatility models, which use spatial weight matrices … limits feasibility of model-estimation to small cross-sections for unstructured models. Structured parametrizations possess … parameters have a direct economic interpretation that reflects the chosen notion of economic classification; iv) model-estimation …

In many multivariate volatility models, the number of parameters increases faster than the cross-section dimension … even solve the curse of dimensionality problem. Identification and estimation of structured specifications are analyzed …