The Analysis Of Dynamic Correlation And Driving Factors Between China And The United States’s Stock Markets

With the economic integration and financial globalization trend of the world is growing, as well as the continuous development of internet information technology, the major international stock markets often show up the phenomenon of up or down simultaneously. The linkage between world’s major stock markets continue to strengthen, researches on the correlation between the stock markets provide important reference values not only in investors to diversify risks, determine the stock price movements and aspects of asset pricing,but also has specific policy implications on Administrating effectively to avoid the stock market fluctuations caused by the external risks to the national financial crisis and achieving the financial market stability. With the development of China’s foreign trade and a series of stock market reform implementations on economic systems, the links between China’s stock market and the world’s major stock market in developed are increasing closely, especially in the U.S. after subprime mortgage crisis, the correlation between China’s stock market and the American stock market shows the new features.Based on the review of the linkage between the domestic and foreign market theory and empirical research literatures,the normative analysis of the inherent linkage between market mechanisms and conduction channels is made, in theory, the correlation between the stock market spread approach is summarized as import and export trade, foreign direct investment, investor psychology and conduction between markets, then the factors which has importment effect on the correlation between the stock market and domestic are analyzed from four aspects. Then we take the yield of 300 Index in Shanghai and Shenzhen and the U.S. Dow Jones index from 2002 to 2013 as the example,at first, examine of the stock market characteristics of volatility by using EGARCH model and derive the conditional volatility for China-US stock markets, thereby using multivariate GARCH-BEKK model to calculate the dynamic correlation coefficients between China and the U.S. stock market, and from the real economic factors, financial factors, macro and micro factors and extreme events factors we analyze the reasons for changes in the dynamic correlation coefficient. On this basis, vector autoregression model,the impulse response and variance decomposition analysis are established between the economic variables relevant with the above factors and dynamic correlation coefficient to investigate the influence two macro-and micro -economic factors have on the dynamic correlation coefficient, the conclusion is that:as emerging stock markets, Shanghai and Shenzhen stock market,like the U.S. stock market volatility, show characteristics of a cluster of volatility, persistence and asymmetry characteristics throughout most of the sample period, the conditional volatility of the CSI 300 Index is larger than the conditional volatility of Dow Jones index. In the factors of China which affect the dynamic correlation between China stock market and United States stock market in the long term, foreign direct investment has a negative impact in related factors between China and the U.S. stock market, dependence on foreign trade and changes of Chinese money supply has a positive influence on the correlation between the stock markets. China’s stock market volatility is the main explanatory variables that affect the correlation between stock markets, which has a larger impact on dynamic correlation coefficient between stock markets; in the factor of America which affect the dynamic correlation between China stock market and United States stock market,in the long term, the changes of money supply and federal funds rate have a positive effect on the correlation.and changes in the U.S. money supply is the main explanatory variable on the stock market correlation.it also has large impact dynamic correlation coefficient between stock markets. Finally, this paper proposed separately based on empirical results to prevent internal and external risks associated policy recommendations.