conditional variances determine the persistence of the transmitted volatility innovations. In particular, the effect of a foreign …This paper analyzes volatility spillovers in multivariate GARCH-type models. We show that the cross-effects between the … volatility innovation on a conditional variance is even more persistent than the effect of an own innovation unless it is offset …

The ranking of multivariate volatility models is inherently problematic because when the unobservable volatility is … the size of the distortion is strictly tied to the level of the accuracy of the volatility proxy. We propose a generalized …

framework. This paper examines the ranking of multivariate volatility models in terms of their ability to forecast out … evaluate the distance between the true covariance matrix and its forecast. The evaluation of multivariate volatility models … requires the use of a proxy for the unobservable volatility matrix which may shift the ranking of the models. Therefore, to …

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on …

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on …

The consistent ranking of multivariate volatility models by means of statistical loss function is a challenging … research field, because it concerns the quality of the proxy chosen to replace the unobserved volatility, the set of competing … realized covariance (RCOV), the proxy that generally provides a consistent estimate of the unobserved volatility. The aim of …

returns and realized volatility (RV), and explore which features of that time-series model contribute to superior density … model of returns and volatility that features two components for log(RV) provides a good fit to Samp;P 500 and IBM data, and …