Dynamic Correlation Analysis Of Data Fluctuation In China's Stock Market And Construction Of Cloud Platform

China's stock market has more than 30 years of history since its opening.Trading systems and regulatory measures have become more and more perfect.Although there is still a certain gap compared with mature foreign stock markets,the fluctuation of yields in China's stock market has always been used as a financial Hot topics in the study.This paper attempts to explore the volatility of the stock market's yield and the correlation between the stock market and the economic market.The research object of this paper is the comprehensive index of China's Shanghai and Shenzhen stock markets and the yield of the stock sector index and the monthly data of CPI,currency issuance and RMB exchange rate in macroeconomic indicators.The research method uses a comprehensive descriptive statistical method and a GARCH family model.The mean,standard deviation,skewness,kurtosis,etc.are analyzed to analyze and evaluate the state of fluctuations.The correlation results show that the data samples exhibit significant fluctuation clustering and non-positive distribution characteristics.The TGARCH model is then applied to analyze the asymmetric leverage effect in the stock composite index and the sector index,from the analysis results,there is a clear phenomenon of the comprehensive sector index,and only some industries exist in the sector index.In the dynamic correlation analysis,this paper uses the DCC-GARCH model to study the Shanghai and Shenzhen composite indices and macroeconomic factors,and horizontally compares the dynamic correlation between the two to explore "the stock market is a barometer of the market economy" Whether the tone is in line with the Chinese market,the results show that there is a significant correlation between stock data and macroeconomic data.And put forward relevant analysis and interpretation,and then make corresponding suggestions from the perspective of investors and policy makers.Rshiny is used to integrate all research data with results to form a web cloud platform for online viewing of research results.Finally,make recommendations from the perspective of investors and policy makers.