Financial Market Connectedness between the U.S. and China: A New Perspective Based on Non-linear Causality Networks

Abstract

This paper analyzes the connectedness between the financial markets in the U.S. and China based on non-linear Granger causality and quantile Granger causality networks. We extend the linear Granger causality network proposed by Billio et al. (2012) and support the importance of multi-class market interactions highlighted by Bollerslev et al. (2018). We find that non-linear Granger causality between stock, bond, and foreign exchange markets in the U.S. and China provides more interconnectedness than linear Granger causality. Both the strength and the direction of the connectedness are related to the quantile of market returns, as evidenced by the fact that the left (right) tail quantiles provide more causal effects than the middle quantiles and the mean. We characterize this phenomenon as the “smiling curve” of causality connectedness, and we show the “smiling curve” for each country and financial submarket. Compared to the financial markets in China, those in the U.S. appear to be more central to the connectedness network, with the main route being the stock market. When market returns are in the right tail quantile interval, the U.S. financial market has more capacity to receive information from various markets than China does. When market returns are in the left tail quantile interval and at the middle quantiles, the Chinese financial markets are more susceptible to shocks than those in the United States, with the Chinese stock and bond markets being more sensitive than the foreign exchange market.