Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH

被引:3
|
作者
Caporin, Massimiliano [1 ]
McAleer, Michael [2 ,3 ,4 ]
机构
[1] Univ Padua, Dept Econ & Management, I-35100 Padua, Italy
[2] Erasmus Univ, Erasmus Sch Econ, Inst Econometr, Rotterdam, Netherlands
[3] Tinbergen Inst, Amsterdam, Netherlands
[4] Kyoto Univ, Inst Econ Res, Kyoto 6068501, Japan
基金
日本学术振兴会; 澳大利亚研究理事会;
关键词
multivariate asymmetry; conditional variance; stationarity conditions; asymptotic theory; multivariate news impact curve; ASYMPTOTIC THEORY; MODELS; STATIONARITY;
D O I
10.1111/j.1467-9574.2010.00479.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
Dynamic Asymmetric Multivariate GARCH (DAMGARCH) is a new model that extends the Vector ARMA-GARCH (VARMA-GARCH) model of Ling and McAleer (2003) by introducing multiple thresholds and time-dependent structure in the asymmetry of the conditional variances. Analytical expressions for the news impact surface implied by the new model are also presented. DAMGARCH models the shocks affecting the conditional variances on the basis of an underlying multivariate distribution. It is possible to model explicitly asset-specific shocks and common innovations by partitioning the multivariate density support. This article presents the model structure, describes the implementation issues, and provides the conditions for the existence of a unique stationary solution, and for consistency and asymptotic normality of the quasi-maximum likelihood estimators. The article also presents an empirical example to highlight the usefulness of the new model.
引用
收藏
页码:125 / 163
页数:39
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