Analysis and Forecast of monthly time Series of Shanghai Stock Index based on ARIMA Model
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The complexity of the influence factors of stock price index, which affect stock price in our country at present stage are the main areas of the bank, bond market and futures market, real estate, currency, etc., from the current trend of the development of the finance and the vast majority of investors in the stock market of numerous financial tools pressing needs, through the establishment of appropriate time series model can achieve rough projections for overall stock prices. This article selects the from China's accession to the WTO in December 2011 to 2014, the Shanghai composite index since July monthly data, through the establishment of ARIMA model adopts the method of static prediction step forward for China's stock market in August 2014, the Shanghai composite index is forecasted, in China 2014 years ago by two quarters showed a trend of rising stock market as a whole. The innovation of this paper is to take the logarithm of the sample data, so as to eliminate the autocorrelation and heteroscedasticity in the time series, and at the same time make the predicted value close to the actual value, the effect is good, hoping to provide a reference for the majority of shareholders.
The Shanghai Composite Index; ARIMA; One step forward static prediction; B-J methodology