Measuring Dependence in China-United States Trade War: A Dynamic Copula Approach for BRICV and US Stock Markets

Abstract

© 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. The phenomena of trade war between China and United States (US) leads us to examine the spillover effects of US stock market volatility on the BRICV stock markets (Brazil, Russia, India, China, and Vietnam). Thus, the dynamic correlations between US and each BRICV stock market, is measured using the flexible dynamic conditional correlations based bivariate GARCH-with-jumps model. The result of both classical bivariate GARCH(1,1) model and bivariate GARCH(1,1)-with-jumps model show that all stock returns have high volatility persistence with the value higher than 0.95. Moreover, the result of DCC-Copula part shows a dynamic correlations between US and each stock in BRICV. We find that the dynamic correlations for all pairs are similar and are not constant. We also find that US stock market has a positive correlations with BRICV stocks between 2012 and 2019. When, we compare the correlations between pre and post trade war in 2018, we observe that bivariate copula between US-China, US-Vietnam and US-Brazil seems to be affected by the trade war as there exhibit a large drop of the correlations after 2018.