Dynamic Interdependence of Stock Returns Based on Information Transmission: Evidence from China and Latin America

This paper analyzes the degree of dynamic interdependence of stock returns between China and six Latin American countries from 2003 to 2018 using the DCC-MGARCH (1,1) model that reflects the information transmission process and the properties of time-varying correlation, such as sensitivity to new information, dependence of past volatility, and the persistence of volatility. It also reports the long-term trends of dynamic interdependence by using rolling window analysis corresponding to a window width of 175 days. The research presents the trends with the United States as a benchmark. First, this paper determined that the Chinese stock market’s influence on the stock markets of six Latin American countries was not decisive. Second, the Chilean and Peruvian stock markets were the most vulnerable to the fluctuations in the Chinese stock returns, while Brazil and Mexico were relatively less affected. Third, the long-term patterns of dynamic conditional correlation between China and the six Latin American countries except for Peru were generally placed between 0.1 and 0.3 Last, when considering the dynamic conditional correlation with the United States as a benchmark, the degree of dynamic interdependence between China and the six Latin American countries was not relatively high.