Return Correlation Between Chinese and US Stock Markets Based on Bivariate Tail Asymmetry Model

DOI: https://doi.org/10.62517/jse.202511301

Author(s)

Xinmeng Hou*, Linping Kong

Affiliation(s)

School of Economics, Guangzhou College of Commerce, Guangzhou, Guangdong, China *Corresponding Author

Abstract

This study selects closing prices of Chinese and US stock market indices as research subjects and constructs a bivariate Gumbel Copula model to investigate the return relation between this two markets. This paper reveals that the closing prices of Chinese and US stock market indices do not follow a normal distribution. By plotting bivariate frequency distribution histograms, the study identifies asymmetric tail risks between the two markets, with sample data primarily concentrated in the upper tail. The bivariate Gumbel Copula model demonstrates superior performance in capturing upper-tail correlations compared to the bivariate normal Copula model. Parameter estimations from the Gumbel Copula model consistently indicate robust positive correlations, whether analyzing the correlation between CSI 300 and S&P 500 indices or the CSI 300 and NASDAQ indices. Tail risk measurements across two sample groups show no significant differences in tail correlation coefficients.

Keywords

Bivariate Gumbel Copula; Chinese Stock Markets; US Stock Market; Return Correlation; Empirical Study

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