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.

引用

页数：12

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