Research on Stock Price Forecasting Based on BP Neural Network

Abstract

With the development and progress of China’s economy and society, China’s stock market has been continuously improved, attracting more and more people to participate in the stock market speculation. No matter the old investors who have been in the stock market for a long time or the new investors who have entered the stock market, they all hope to be able to predict the stock price through technical means. This is also a problem that global stock market participants are paying attention to, which attracts numerous researchers to study it, and also produces a lot of research results, such as time series prediction method. There are many factors that affect the stock price. If we want to improve the accuracy of stock measurement, we must first understand the factors that affect the stock, and make scientific and reasonable use of these factors for price prediction to obtain more ideal results. Using BP neural network method to forecast and analyze the stock price can give full play to the advantage of BP neural network algorithm based on error reverse propagation, so as to reduce the interference factors of stock price prediction. It can be seen that BP neural network is of great help to predict the stock price through the research on the history of stock price operation. In this paper, the stock price prediction of BP neural network is studied, and it is concluded that the reasonable and efficient use of BP neural network system has played a great role in the stock price prediction and analysis. It is expected that the research will make a contribution to the development of China’s stock market.