Beijing University of Posts and Telecommunications, Beijing, China
The purpose of forecasting the rise and fall of the stock market is for investors to analyze the future stock price trends, trends and other information, and combine the characteristics of the stocks to choose appropriate methods to make trading decisions. The purpose of this paper to study the stock price prediction model is to improve the preventive measures against stock risks. This article mainly uses the experimental method and the comparative method to conduct an experimental research on the stock price fluctuation forecast model. Experimental results show that the accuracy of BP neural network algorithm in stock prediction can reach 91.5%. This means that the stock price prediction model based on BP neural network has certain feasibility, and its research value is also relatively large.
BP neural network, Stock rise and fall, Forecast model, System design
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