Whittle estimation in multivariate CCC-GARCH processes

被引：2

作者：

Bibi, Abdelouahab ^{[1
]}

Kimouche, Karima ^{[1
]}

机构：

[1] Univ Constantine Skikda, Dept Math, Skikda, Algeria

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2019年 / 48卷 / 15期

关键词：

Multivariate CCC-GARCH models; stationarity; whittle estimator; consistency; asymptotic normality; ASYMPTOTIC THEORY;

D O I：

10.1080/03610926.2018.1484140

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：

In this paper, we explore some probabilistic properties and statistical analysis of multivariate constant conditional correlation GARCH (CCC-GARCH for short) model. So, in the first part we give the conditions for the model stationarity and its finite moments up to some orders. In the second part, the Whittle estimator is proposed for the parameters CCC-GARCH model based on a transformation. This Whittle estimator is shown to be consistent when the data have finite 4th moment, and its asymptotic normality is established when the data have finite 8th moment. Finite sample properties of this Whittle estimator are further examined through Monte-Carlo experiments.

引用

页码：3921 / 3940

页数：20

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