Analysis of the Correlation Between Chinese and American Stock Markets Based on VAR Model

Abstract

This study investigates the correlation between Chinese and American stock markets during the post-pandemic era, employing a Vector Autoregression (VAR) model and analyzing data from the SSEC Index and S&P 500 Index spanning from April 9th, 2019, to April 3rd, 2024. The analysis reveals stationary behavior in both indexes and highlights a bi-directional influence between them, with the S&P 500 exerting a notably stronger impact on the SSEC. Impulse response analysis indicates that following a shock to the S&P 500, the SSEC responds after approximately 20 days, while a shock to the SSEC results in a lagged response of about 23 days in the S&P 500. Variance decomposition analysis underscores the dominance of endogenous shocks, with SSEC's shocks accounting for approximately 98% of its forecast error variance and S&P 500's shocks contributing to about 97% of its forecast error variance. The declining trend in forecast error variance contribution over time suggests an increasing certainty and accuracy in the model's predictions regarding the relationship between these markets. These insights provide valuable guidance for investors, policymakers, and researchers navigating the complexities of the post-pandemic financial landscape.