Pseudo maximum-likelihood estimation of the univariate GARCH (1,1) and asymptotic properties

被引：0
|
作者：
Kouassi, Eugene [1 ]
Soh, Patrice Takam [2 ]
Brou, Jean Marcelin Bosson [3 ]
Ndoumbe, Emile Herve [2 ]
机构：
[1] West Virginia Univ, Resource Econ, Morgantown, WV 26506 USA
[2] Univ Yaounde I, Dept Math, Yaounde, Cameroon
[3] Univ Felix Houphouet Boigny, Dept Econ, Abidjan, Cote Ivoire
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2017年 / 46卷 / 20期
关键词：
pseudo-maximum-likelihood; estimationstrong consistencyGARCH (1,1); asymptotic normality; Martingales' techniques; ARCH MODELS; VARIANCE; QMLE;
D O I：
10.1080/03610926.2016.1231824
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
One provides in this paper the pseudo-likelihood estimator (PMLE) and asymptotic theory for the GARCH (1,1) process. Strong consistency of the pseudo-maximum-likelihood estimator (MLE) is established by appealing to conditions given in Jeantheau (1998) concerning the existence of a stationary and ergodic solution to the multivariate GARCH (p, q) process. One proves the asymptotic normality of the PMLE by appealing to martingales' techniques.
引用
收藏
页码：10253 / 10271
页数：19
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