Research On The Volatility Of Shanghai Stock Aggregate Ind X And The Relationship With Maeroeeonomie Variables

After more than thirty years of reform and opening sustained development, China’s economy has made remarkable achievements and become the second largest after the United States economy. But compared to other developed countries, China’s capital market is still relatively backward. Complementarity between all know, the capital market and the real economy, the capital markets to the real economy is not only the product of a certain stage, it is able to produce healthy and stable development has an important impact on the smooth running of the real economy. Therefore, it is to judge whether or not the stable development of China’s national economy has important significance for the study of the stability of the capital market. For now, the stock market importance of our national economy is self-evident, therefore, study the volatility of the stock market volatility based research has become an important aspect of the capital market stability. Factors affecting stock prices intricate, divided into micro and macro aspects, from the micro level, the stock price volatility is mainly affected by the company’s fundamentals, investors, investment preferences and other factors; from the macro level, mainly due to stock price volatility national economic policy, macro-economic climate and other factors influence. This paper selects the Shanghai Composite Index for the study, to carry out empirical research on China’s stock market volatility problems.First, select the volatility and the volatility of the monthly income of January 1997 to December 2014 in the Shanghai Composite Index daytime earnings (Guotai Junan provided) as the research object, through daily and monthly yield average yield of image feature judgment, find out the fluctuation characteristics, and then were stata software through statistics GARCH (1,1) model MGARCH (1,1) model EGARCH (1,1) model TGARCH (1,1) coefficient and maximum likelihood model of statistical LL, AIC, BIC value, according to the LL maximum AIC, BIC Min choose the most appropriate rate of return on the Shanghai Composite Index volatility characteristics of the model, and finally select the EGARCH (1,1) model.Secondly, the use of some macroeconomic variables in January 1997 to December 2014 period (including access to places, the consumer price index, money supply, government expenditure, etc.) monthly data for the study, its first PP unit root test, and then based on the existence of PP unit root test results on the number of data processing and the number of check points on treatment. Obtaining its basic statistics and OLS regression variables treated them, and finally apply Granger causality test them. Do an overall regression, because Granger test between dependent and independent variables because of the relationship.Finally, the monthly fluctuation data and macroeconomic variables we use the Shanghai Composite Index on average monthly yield performs vector autoregression (VAR), determined their relationship volatility, and ultimately come to the volatility of economic variables and the Shanghai Composite Index Volatility Conclusion The relationship between the following:the impact of stock market volatility volatility of public expenditure growth without fluctuation housing sales area relative value and volatility of the stock market does not significantly affect the relationship between each other, the difference between the relative value of import and export volatility and stock No market volatility significantly interaction Volatility, CPI relative value volatility and stock market mutual influence, historical volatility CPI relative value will affect the volatility of the stock market fluctuate stock of CPI relative value also have some predict.