The Dynamic Correlation of Stock Markets in the World’s Five Largest Economies—Based on DCC-GARCH Model

The dynamic correlation of stock markets in various countries has attracted the attention of scholars and financial investors. In this paper, the dynamic conditional correlation model and the generalized autoregressive conditional heteroskedasticity model are combined to analyze the dynamic conditional correlation coefficient matrix of the stock data of China, the United States, Britain, Germany and Japan, aiming at the five indexes of the Shanghai Securities Composite Index, the Dow Jones Index, the Financial Times Stock Exchange 100 Index, the Frankfurt DAX Index and the Nikkei Index. The results show that there is a certain correlation between the stock markets of various countries, especially the correlation coefficient of the yield of the FTSE index and the GDAXI index reaches 0.96, which a strong correlation. The conclusions of this study can provide constructive suggestions for global economic recovery.