A Study On The Price Porecast Of Shanghai And Shenzhen 300 Stock Index Futures

The CSI 300 stock index futures is a derivative financial instrument that can avoid systemic risk.Since its listing on April 16,2010,it has attracted the attention of investors.The traditional stock spot market only has one-way trading mechanism for bargain-hunting,while the CSI 300 stock index futures have a two-way trading mechanism with speculative,hedging,and arbitrage functions,providing derivative financial services for the stock market to avoid systemic risks.Because the stock index futures trading has leverage,speculators and hedgers face a greater risk of price fluctuation,especially when extreme market,Shanghai and shenzhen300 index futures huge fluctuations can bring huge losses to investors.How to analyze the changing trend of CSI 300 stock index and avoid bringing huge losses to investors is an extremely important research field of financial market science.First of all,this paper introduces the basic knowledge of stock index futures.The system elaborates the traditional forecasting method of financial market and combs the modern forecasting model of financial market.Through comparative analysis,the arma-garch model is established for empirical research.The specific contents of this paper is as follows:firstly,based on the current economic situation,we analyze the trend of the futures price of csi 300 index futures.Secondly,the paper expounds the technical analysis method of csi 300 index futures.Finally,conduct empirical research to draw conclusions and make recommendations.The process of empirical research in this paper is to select the daily closing price of CSI 300 stock index futures from April 16,2010 to Decmber 8,2017 as the original data and take the logarithmic rate of return as the research variable.The predictive test is carried out first,and proved that the data can be predicted.Then the unit root test is done,and the sequence is stable.After the sequence autocorrelation test,the ARMA model order was determined by AIC and SC criterion,and the ARCH effect test was performed to prove that there existed the ARCH effect and the GARCH model was established.GARCH family model includes GARCH,EGARCH and TGARCH.The residuals of these models are derived from normal distribution,student-t distribution and GED distribution,respectively.The ARMA model is combined with each model of the GARCH family in the case of different distributions,and the optimal model is obtained by comparativeanalysis.Finally,the sample prediction is carried out,and the applicability of the model is determined according to the residual error.Again outside the sample forecast.Then we need to make an out-of-sample forecast,select the daily closing price data from Decmber 12,2017 to March 12,2018 are compared with the predicted values obtained by using the model,and the accuracy of the model is judged by combining the prediction error index RMS root error(RMSE)with the mean absolute error(MAE).