Asymptotic theory for multivariate GARCH processes

被引：141

作者：

Comte, F ^{[1
]}

Lieberman, O

机构：

[1] Univ Paris 05, CNRS, FRE 2428, Lab MAP5, F-75270 Paris 06, France

[2] Technion Israel Inst Technol, Fac Ind Engn & Management, IL-32000 Haifa, Israel

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2003年 / 84卷 / 01期

关键词：

asymptotic normality; BEKK; consistency; GARCH; Martingale CLT;

D O I：

10.1016/S0047-259X(02)00009-X

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：

We provide in this paper asymptotic theory for the multivariate GARCH(p, q) process. Strong consistency of the quasi-maximum likelihood estimator (MLE) is established by appealing to conditions given by Jeantheau (Econometric Theory 14 (1998), 70) in conjunction with a result given by Boussama (Ergodicity, mixing and estimation in GARCH models, Ph.D. Dissertation, University of Paris 7, 1998) concerning the existence of a stationary and ergodic solution to the multivariate GARCH(p, q) process. We prove asymptotic normality of the quasi-MLE when the initial state is either stationary or fixed. (C) 2003 Elsevier Science (USA). All rights reserved.

引用

页码：61 / 84

页数：24

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