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

  • Leovardo Mata Mata(corresponding author)
    ,
  • José Antonio Núñez Mora
    ,
  • Ramona Serrano Bautista
*Corresponding author for this work
Research Output:
Contribution to journal
Article
Peer-review

Open access

Publication Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Journal (Volume, Issue Number)

SAGE Open (Volume 11, Issue 2)

Publication milestones

  • Published - 2021

Publication status

Published - 2021

Publication IDs

  • 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.