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

页码：10253 / 10271

页数：19

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