This paper provides an alternative formulation of the conditional correlation structure in fitting the multivariate GARCH model. A special case is the multivariate ARCH model with random coefficients. Its coherence structure is derived by the correlations between the random coefficients which play an important role in describing the interested heteroscedastic features. The parameter estimation problem can be solved by maximum likelihood estimation and model selection is via the likelihood ratio test. We consider three real applications: (1) the spot and forward rates of the Deutsche Mark against the US dollars; (2) exchange rates of Deutsche Mark and Japanese Yen against US dollars; (3) the Heng Sang index and SES index. © 2005 Elsevier B.V...
The likelihood of multivariate GARCH models is ill-conditioned because of two facts. First, financia...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...
In this paper it is shown that the popular Autoregressive Conditional Heteroscedasticity (ARCH) mode...
We study multivariate ARCH and GARCH models and their subsequent application to simulated and real d...
A multivariate time series model with time varying conditional variances and covariances, but consta...
96 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.This thesis presents a test st...
96 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.This thesis presents a test st...
This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We p...
A new approach is proposed to estimate a large class of multivariate volatility models. The method ...
In this paper we propose a new multivariate GARCH model with time-varying conditional correlation st...
In this paper we propose a new multivariate GARCH model with time-varying conditional correlation st...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...
The likelihood of multivariate GARCH models is ill-conditioned because of two facts. First, financia...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...
In this paper it is shown that the popular Autoregressive Conditional Heteroscedasticity (ARCH) mode...
We study multivariate ARCH and GARCH models and their subsequent application to simulated and real d...
A multivariate time series model with time varying conditional variances and covariances, but consta...
96 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.This thesis presents a test st...
96 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.This thesis presents a test st...
This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We p...
A new approach is proposed to estimate a large class of multivariate volatility models. The method ...
In this paper we propose a new multivariate GARCH model with time-varying conditional correlation st...
In this paper we propose a new multivariate GARCH model with time-varying conditional correlation st...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatil...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...
The likelihood of multivariate GARCH models is ill-conditioned because of two facts. First, financia...
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper s...
We introduce two multivariate constant conditional correlation tests that require little knowledge o...