- 期刊
Research and Investment Model of Stock Index Fluctuation based on Entropy Method
摘要
Stock index fluctuation is a complex nonlinear process, which should be improved by considering other factors besides the advancement of it with the uniform time process. In this paper, a stock turnover prediction model based on time series analysis will be constructed based on the regularity research of stock in the stock market. Through factor analysis dimension reduction, the influential variables are found out and the investment index model is constructed. The entropy method is used to assess whether there are differences in parameters. If there are differences, the optimization model is needed to be optimized. If the parameters are relatively perfect, the model does not need to be optimized, so as to evaluate the scale of the model. The parameters of the stock investment index model are modified by an entropy method to achieve the model optimization effect. Finally, through the stock yield sequence analysis of the trend of stock volatility effect, build the ARIMA model forecast analysis for the coming year index fluctuation, can be used in the index of the current fluctuations and next year's index analysis and prediction of investment for the future of its positive volatility will benefit, the opposite is not conducive to future investment, summed up the short-term investment direction, the section chief and investment advice and strategies.