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

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...

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Bibliographic Details
Published in:SAGE open 2021-04, Vol.11 (2)
Main Authors: Mata, Leovardo Mata, Núñez Mora, José Antonio, Serrano Bautista, Ramona
Format: Article
Language:English
Subjects:
Securities markets
Stock exchanges
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Summary: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.
ISSN:2158-2440
2158-2440
DOI:10.1177/21582440211009509