Pseudo maximum likelihood estimation and asymptotic results of the GARCH (1,2) Model under dependent innovations

被引：0

作者：

Takam, Patrice Soh ^{[1
]}

Kouassi, Eugene ^{[2
]}

Fadonougbo, Renaud ^{[3
]}

Brou, Jean Marcelin Bosson ^{[4
]}

Mougoue, Mbodja ^{[5
]}

机构：

[1] Univ Montpellier, Dept Math, Montpellier, France

[2] West Virginia Univ, Resource Econ, Morgantown, WV 26506 USA

[3] Pan African Univ, Inst Basic Sci Technol & Innovat, Nairobi, Kenya

[4] Univ FHB, Dept Econ, Abidjan, Cote Ivoire

[5] Wayne State Univ, Dept Finance, Detroit, MI 48202 USA

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2020年 / 49卷 / 08期

关键词：

Asymptotic normality; Consistency; Dependent innovations; GARCH model; Monte Carlo results; Pseudo-maximum likelihood; Quadratic exponential families; 60G; NORMALITY; VARIANCE;

D O I：

10.1080/03610918.2018.1513140

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：

This paper deals with the pseudo maximum likelihood estimation of a GARCH (1,2) model under two reasonably weak, realistic and tractable assumptions: the innovations are dependent albeit conditionally independent, and belong to the quadratic exponential family, which contains several standard distributions. More specifically, the paper derives the consistency and asymptotic normality of the pseudo maximum likelihood estimator (PLME hereafter) under some regularity conditions by means of martingale techniques. Finally, extensive Monte Carlo experiments are conducted to examine the finite sample performance of the proposed PMLE.

引用

页码：2134 / 2163

页数：30

共 20 条

[1] Pseudo maximum likelihood estimation of structural models involving fixed-point problems [J].