Author: L. Bauwens
Publisher:
ISBN:
Category :
Languages : en
Pages : 22
Book Description
On the Weak Consistency of the Quasi-maximum Likelihood Estimator in Var Models with Bekkk-Garch (1,q) Errors
On the Weak Consistency of the Quasi-maximum Likelihood Estimator in VAR Models with BEKK-GARCH(1,q) Errors
Author: Luc Bauwens
Publisher:
ISBN:
Category : Error analysis (Mathematics)
Languages : en
Pages : 22
Book Description
Publisher:
ISBN:
Category : Error analysis (Mathematics)
Languages : en
Pages : 22
Book Description
On the Weak Consistency of the Quasi Maximum Likelihoop Estimator in Var Models with Bekk-garch (1,q) Errors
Consistency of Quasi-maximum Likelihood Estimators for the Reduced Regime-switching GARCH Models
Consistency of Quasi-maximum Likelihood Estimators for the Regime-switching GARCH Models
Consistency of Quasi-Maximum Likelihood Estimators for Models with Conditional Heteroskedasticity
Author: Whitney K. Newey
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Virtually all empirical studies that assume a time-varying conditional variance use a quasi-maximum likelihood estimator (QMLE). If the density from which the likelihood is constructed is assumed to be Gaussian, the QMLE is known to be consistent under correct specification of both the conditional mean and conditional variance. We show that if both the assumed density and the true density are symmetric a QMLE remains consistent. If, however, either the assumed density or the true density is asymmetric, a QMLE is generally not consistent. To ensure that a QMLE is consistent under asymmetric densities, we include the conditional standard deviation as a regressor. We calculate the efficiency loss associated with the added regressor if the densities are symmetric and show that for a QMLE of the conditional variance parameters of a GARCH process there is no efficiency loss. Finally, we develop a test of consistency of a QMLE from the significance of the additional regressor.
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Virtually all empirical studies that assume a time-varying conditional variance use a quasi-maximum likelihood estimator (QMLE). If the density from which the likelihood is constructed is assumed to be Gaussian, the QMLE is known to be consistent under correct specification of both the conditional mean and conditional variance. We show that if both the assumed density and the true density are symmetric a QMLE remains consistent. If, however, either the assumed density or the true density is asymmetric, a QMLE is generally not consistent. To ensure that a QMLE is consistent under asymmetric densities, we include the conditional standard deviation as a regressor. We calculate the efficiency loss associated with the added regressor if the densities are symmetric and show that for a QMLE of the conditional variance parameters of a GARCH process there is no efficiency loss. Finally, we develop a test of consistency of a QMLE from the significance of the additional regressor.
Quasi-maximum Likelihood Estimators in GARCH(1,2) Model
Consistency of Quasi Maximum Likelihood Estimators for Models with Conditional Heteroscedasticity
Maximum Probability Estimators and Related Topics
Author: L. Weiss
Publisher: Lecture Notes in Mathematics
ISBN:
Category : Computers
Languages : en
Pages : 124
Book Description
Publisher: Lecture Notes in Mathematics
ISBN:
Category : Computers
Languages : en
Pages : 124
Book Description
On Maximum Likelihood Estimation (MLE) of Classical Errors in Variables Models and Generalized Errors in Variables Models
Author: Yngve Willassen
Publisher:
ISBN: 9788257080600
Category : Estimation theory
Languages : en
Pages : 10
Book Description
Publisher:
ISBN: 9788257080600
Category : Estimation theory
Languages : en
Pages : 10
Book Description