We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a nonparametric long run component and a unit multivariate GARCH short run dynamic component. We suggest various kernel-based estimation procedures for the parametric and nonparametric components, and derive the asymptotic properties thereof. For the parametric part of the model, we obtain the semiparametric efficiency bound. Our method is applied to a bivariate stock index series.We find that the univariate model of Engle and Rangel(2008) appears to be violated in the data whereas our multivariate model is more consistent with the data
The importance of modelling comovements of financial returns is well established in the literature. ...
We statistically analyse a multivariate HJM diffusion model with stochastic volatility. The volatili...
Abstract. This paper investigates the estimation of a wide class of multivariate volatility mod-els....
We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel ...
We propose a multivariate generalization of the multiplicative volatility model ofEngle and Rangel (...
In this article, we study a semiparametric multiplicative volatility model, which splits up into a n...
Estimation of multivariate volatility models is usually carried out by quasi max-imum likelihood (QM...
textabstractEstimation of multivariate volatility models is usually carried out by quasi maximum lik...
This article presents theoretical and empirical methodology for estimation and modeling of multivari...
In this paper, semiparametric methods are applied to estimate multivariate volatility functions, usi...
A new multivariate volatility model that belongs to the family of conditional correlation GARCH mode...
This thesis deals with the formulation and estimation of the multivariate GARCH model. It mentions t...
We introduce a multivariate stochastic volatility model that imposes no restrictions on the structur...
Abstract The class of Multivariate BiLinear GARCH (MBL-GARCH) models is proposed and its statistica...
textabstractQuasi maximum likelihood estimation and inference in multivariate volatility models rema...
The importance of modelling comovements of financial returns is well established in the literature. ...
We statistically analyse a multivariate HJM diffusion model with stochastic volatility. The volatili...
Abstract. This paper investigates the estimation of a wide class of multivariate volatility mod-els....
We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel ...
We propose a multivariate generalization of the multiplicative volatility model ofEngle and Rangel (...
In this article, we study a semiparametric multiplicative volatility model, which splits up into a n...
Estimation of multivariate volatility models is usually carried out by quasi max-imum likelihood (QM...
textabstractEstimation of multivariate volatility models is usually carried out by quasi maximum lik...
This article presents theoretical and empirical methodology for estimation and modeling of multivari...
In this paper, semiparametric methods are applied to estimate multivariate volatility functions, usi...
A new multivariate volatility model that belongs to the family of conditional correlation GARCH mode...
This thesis deals with the formulation and estimation of the multivariate GARCH model. It mentions t...
We introduce a multivariate stochastic volatility model that imposes no restrictions on the structur...
Abstract The class of Multivariate BiLinear GARCH (MBL-GARCH) models is proposed and its statistica...
textabstractQuasi maximum likelihood estimation and inference in multivariate volatility models rema...
The importance of modelling comovements of financial returns is well established in the literature. ...
We statistically analyse a multivariate HJM diffusion model with stochastic volatility. The volatili...
Abstract. This paper investigates the estimation of a wide class of multivariate volatility mod-els....