Multivariate Distribution in the Stock Markets of Brazil, Russia, India, and China
- Leovardo Mata Mata(corresponding author),
- José Antonio Núñez Mora,
- Ramona Serrano Bautista
- ,
- ,
- Instituto Tecnologico de Estudios Superiores de Monterrey,
- Universidad Panamericana (UP)
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Research Output:
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Article
Peer-reviewOriginal language
EnglishJournal (Volume, Issue Number)
SAGE Open (Volume 11, Issue 2)Publication milestones
- Published - 2021
Publication status
Published - 2021
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- Scopus: 85105400056
Abstract
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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