9卷 第1期
1.Xi'an Polytechnic University, Xi'an, 710600, China
2.Hebei Vocational University of Industry and Technology, Shijiazhuang, 050091, China
纸质出版日期：2025-01-21
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(2025). Risk spillover between financial markets based on non-parametric quantile Vine-Copula model. 发展经济学, 9(1), 90-94.
Wang Mengwei,Lu Junxiang,Zheng Yu,et al.Risk spillover between financial markets based on non-parametric quantile Vine-Copula model[J].Development Economics of China,2025,09(01):90-94.
(2025). Risk spillover between financial markets based on non-parametric quantile Vine-Copula model. 发展经济学, 9(1), 90-94. DOI： 10.47297/wspdecWSP2515-797318.20250901.
Wang Mengwei,Lu Junxiang,Zheng Yu,et al.Risk spillover between financial markets based on non-parametric quantile Vine-Copula model[J].Development Economics of China,2025,09(01):90-94. DOI： 10.47297/wspdecWSP2515-797318.20250901.
Brics (China
Brazil
Russia
India
South Africa) as the world's emerging economies
the stability of their financial markets has an important impact on the global economy. This paper intends to study the correlation structure and risk contagion effect among the financial markets of the BRICS countries. Based on the stock market
an important indicator of the financial markets of each country
the paper uses the non-parametric quantile model to fit the marginal distribution of the returns of each country
constructs the D-Vine Copula model
explores the correlation structure among the financial markets of each country
and uses CoES to describe the risk spillover intensity. The empirical results show that China's financial market has significant risk spillover effect on other BRICS countries
and the impact on Russia is the most prominent
followed by India and South Africa
and the impact on Brazil is relatively weak and presents obvious asymmetry. These results have important theoretical value and practical significance for monitoring the risk contagion effect in BRICS countries.
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