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Research On Macro Influencing Factors Of Long-Term Correlation Between Chinese And American Stock Markets

Posted on:2020-10-31Degree:MasterType:Thesis
Country:ChinaCandidate:H X SiFull Text:PDF
GTID:2439330596481362Subject:Financial engineering
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With the continuous development of economic globalization and financial globalization,the link between international stock market is also showing a growing trend,Chinese stock market is the second largest stock market in the world,the United States as the world's biggest stock market,The correlation between the two markets is the focus of investors and regulators.The stock market is the macroeconomic "barometer",the macroeconomic development of the two countries can be intuitively reflected in the stock market,In recent years,China and the United States have closely linked macroeconomic relations.China has become the largest trading partner of the United States and the largest source of imports.The United States is also China's second largest trading partner and the largest export market.Economic ties between the two countries will be getting closer and closer.But since Trump took office,he has formulated a series of policies affecting the trade relations between the two countries,which has a certain degree of impact on the trade exchanges between the two countries,and the trade war between China and the United States has a different degree of impact on the stock markets of the two countries.Therefore,this paper focuses on the impact of macro economy on China-US stock market's volatility and correlation.The research is mainly carried out from three aspects,first using the same frequency data to study the fluctuation spillover effect between the Chinese and American stock markets,then using the mixed-frequency data to extract the long-term volatility component and short-term volatility component in the Chinese and American stock markets,and analyze the effect of macroeconomic variables on the long-term volatility.Finally,the long-term dynamic correlation and short-term dynamic correlation in China-US stock market are extracted by using mixed-frequency data,and the influence of macroeconomic variables is compared and analyzed.Conclusion: Based on the Bekk-garch model,this paper studies the volatility spillover effect of Chinese and American stock markets,and the empirical results show that the arch effect and garch effect of both markets are significant,that is,there is a two-way fluctuation spillover effect between Chinese and American stock markets,and it has both short-term impact effect and long-term lasting effect.Based on the mixed-frequency data model,this paper studies the influence of macroeconomics on the long-term volatility of China-US stock market,and the empirical results show that CPI growth rate,M2 growth rate,Chinese FDI growth rate and trade intensity enhance the long-term volatility of Chinese and American stock markets,and the GDP growth rate weakens the long-term volatility of Chinese stock market,but strengths the American stock market's.Among them,trade intensity and GDP growth rate have the most significantly effect in both markets.Then,the long-term dynamic correlation coefficient and short-term dynamic correlation coefficient of Chinese and American stock markets were extracted.The long-term dynamic correlation coefficient was generally on the rise,and the correlation was significantly enhanced during the financial subprime crisis in 2007.Finally,the paper studies the impact of macroeconomics on the long-term dynamic correlation between Chinese and American stock markets.The macroeconomic fundamental growth rate difference and Chinese FDI growth rate are negatively correlated with long-term dynamic correlation.China-US trade intensity is positively correlated with long-term correlation,and Compared with the fundamentals,Chinese FDI growth rate and trade intensity have a greater impact on the long-term dynamic correlation coefficient.
Keywords/Search Tags:macro economy, Sino-US stock market, DCC-MIDAS model, Long-term volatility, Long-term dynamic correlation
PDF Full Text Request
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