Two tests for multivariate conditional heteroscedastic models are proposed. One is based on the cross-correlations of standardized squared residuals and the other is a score (Lagrange multiplier) test. The cross-correlations test can be used to detect the presence of multivariate conditional heteroscedasticity whereas the other test can be used for diagnostic checking. Simulation studies on the size and power of the test statistics are reported. The application of the tests is illustrated by an example using the S & P 500 and Sydney All Ordinary Indexes.Department of Applied Mathematic
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
Traditional tests for conditional heteroscedasticity are based on testing for significant autocorrel...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
Two tests for multivariate conditional heteroscedastic models are proposed. One is based on the cros...
Abstract: We examine the residual-based diagnostics for univariate and multivari-ate conditional het...
10.1016/S0378-4754(03)00125-3Mathematics and Computers in Simulation641113-119MCSI
Multivariate conditional heteroscedasticity models form an important class of nonlinear time series ...
In the present paper a family of bivariate distributions characterized by standardized symmetric con...
This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We p...
A Lagrange multiplier test for testing the parametric structure of a constant conditional correlatio...
A Lagrange multiplier test for testing the parametric structure of a constant conditional correlatio...
The double autoregressive model finds its use in the modelling of conditional heteroscedasticity of ...
This paper proposes a convenient and generally applicable diagnostic m-test for checking the distrib...
Traditional tests for conditional heteroscedasticity are based on testing for significant autocorrel...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
Traditional tests for conditional heteroscedasticity are based on testing for significant autocorrel...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
Two tests for multivariate conditional heteroscedastic models are proposed. One is based on the cros...
Abstract: We examine the residual-based diagnostics for univariate and multivari-ate conditional het...
10.1016/S0378-4754(03)00125-3Mathematics and Computers in Simulation641113-119MCSI
Multivariate conditional heteroscedasticity models form an important class of nonlinear time series ...
In the present paper a family of bivariate distributions characterized by standardized symmetric con...
This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We p...
A Lagrange multiplier test for testing the parametric structure of a constant conditional correlatio...
A Lagrange multiplier test for testing the parametric structure of a constant conditional correlatio...
The double autoregressive model finds its use in the modelling of conditional heteroscedasticity of ...
This paper proposes a convenient and generally applicable diagnostic m-test for checking the distrib...
Traditional tests for conditional heteroscedasticity are based on testing for significant autocorrel...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...
Traditional tests for conditional heteroscedasticity are based on testing for significant autocorrel...
This paper proposes a convenient and generally applicable diognostic m-test for checking the distrib...