TY - JOUR
T1 - Multivariate Distribution in the Stock Markets of Brazil, Russia, India, and China
AU - Mata, Leovardo Mata
AU - Núñez Mora, José Antonio
AU - Serrano Bautista, Ramona
N1 - Publisher Copyright:
© The Author(s) 2021.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - 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.
AB - 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.
KW - BRIC
KW - dependency
KW - multivariate normal inverse Gaussian distribution
KW - stock returns
UR - http://www.scopus.com/inward/record.url?scp=85105400056&partnerID=8YFLogxK
U2 - 10.1177/21582440211009509
DO - 10.1177/21582440211009509
M3 - Artículo
AN - SCOPUS:85105400056
SN - 2158-2440
VL - 11
JO - SAGE Open
JF - SAGE Open
IS - 2
ER -