Abstract
Stocks are an important part of the national economy. With the increase of liquidity in people's hands, more and more people choose to enter the stock market. In stock investment, accurate prediction of stock price index is not only of great significance to investors, but also of promoting the development of my country's stock market. It even has an important role in accelerating my country's economic development. The paper chose the ARIMA method based on linear technology for time series forecasting and the NN model that is good at mining the implicit nonlinear relationship in the data to compare the China Sea Securities Composite Index from January 21, 2020 to December 31, 2020. Empirical analysis of closing prices and short-term forecasts are made.
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