Estimation of multivariate asymmetric power GARCH models

被引：3
|
作者：
Boubacar Mainassara, Y. [1 ]
Kadmiri, O. [1 ]
Saussereau, B. [1 ]
机构：
[1] Univ Bourgogne Franche Comte, Lab Math Besancon, CNRS, UMR 6623, 16 route Gray, F-25030 Besancon, France
来源：
JOURNAL OF MULTIVARIATE ANALYSIS | 2022年 / 192卷
关键词：
Constant conditional correlation; Multivariate asymmetric power GARCH; models; Quasi -maximum likelihood; Threshold models; CONDITIONAL CORRELATION; ASYMPTOTIC THEORY; QML ESTIMATION; INFERENCE; HETEROSKEDASTICITY; VOLATILITY; TESTS;
D O I：
10.1016/j.jmva.2022.105073
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 suggest a new class of multivariate power transformed asymmetric models. It includes several functional forms of multivariate GARCH models which are of great interest in financial modeling and time series literature. We provide an explicit necessary and sufficient condition to establish the strict stationarity of the model. The asymptotic properties of the quasi-maximum likelihood estimator of the parameters are established. The asymptotic results are illustrated by Monte Carlo experiments and an application to real financial data is studied. (C) 2022 Elsevier Inc. All rights reserved.
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页数：19
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