Normal mixture quasi maximum likelihood estimation for non-stationary TGARCH(1,1) models
Wang, Hui and Pan, Jiazhu (2014) Normal mixture quasi maximum likelihood estimation for non-stationary TGARCH(1,1) models. Statistics and Probability Letters, 91. 117–123. ISSN 0167-7152 (https://doi.org/10.1016/j.spl.2014.03.027)
Preview |
Text.
Filename: Wang_Pan_SPL_2014_Normal_mixture_quasi_maximum_likelihood_estimation.pdf
Accepted Author Manuscript License: Download (137kB)| Preview |
Abstract
Although quasi maximum likelihood estimator based on Gaussian density (G-QMLE) is widely used to estimate GARCH-type models, it does not perform successfully when error distribution is either skewed or leptokurtic. This paper proposes normal mixture quasi-maximum likelihood estimator (NM-QMLE) for non-stationary TGARCH(1,1) models. We show that, under mild regular conditions, there is no consistent estimator for the intercept, and the proposed estimator for any other parameter is consistent.
-
-
Item type: Article ID code: 49282 Dates: DateEvent1 August 2014Published12 April 2014Published Online18 March 2014AcceptedSubjects: Science > Mathematics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 17 Sep 2014 15:36 Last modified: 21 Feb 2024 14:42 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/49282