Multivariate Distribution in the Stock Markets of Brazil, Russia, India, and China

被引：2
|
作者：
Mata Mata, Leovardo [1 ]
Nunez Mora, Jose Antonio [2 ]
Serrano Bautista, Ramona [3 ]
机构：
[1] Univ Anahuac Mexico, Av Univ Anahuac 46, Anahuac 52786, Huixquilucan, Mexico
[2] Tecnol Monterrey, EGADE Business Sch, Ciudad De Mexico, Mexico
[3] Univ Panamer, Zapopan, Mexico
来源：
SAGE OPEN | 2021年 / 11卷 / 02期
关键词：
dependency; BRIC; multivariate normal inverse Gaussian distribution; stock returns; EMPIRICAL DISTRIBUTIONS; DYNAMIC CORRELATIONS; BRICS; RETURNS; OIL; SPILLOVERS; RISK; GOLD;
D O I：
10.1177/21582440211009509
中图分类号：
C [社会科学总论];
学科分类号：
03 ; 0303 ;
摘要：
The purpose of this article is to analyze the dependence between Brazil, Russia, India, and China (BRIC) stock markets, adjusting the multivariate Normal Inverse Gaussian probability distribution (NIG) in 2010-2019 on data yields. Using the estimated parameters, a robust estimator of the correlation matrix is calculated, and evidence is found of the degree of integration in BRIC financial markets during the period 2000-2019. In addition, it is found that the Value at Risk presents a better performance when using the NIG distribution versus multivariate generalized autoregressive conditional heteroscedastic models.
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页数：12
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