Abstract
The Shanghai and Shenzhen 300 Index covers the epitome of 60% of the Shanghai and Shenzhen stock markets, and is a high-level summary of the Shanghai and Shenzhen stock markets. If we can predict the closing price of the Shanghai and Shenzhen 300 Index, it will guide the investment of the Shanghai and Shenzhen stock markets, promote the sound development of the stock market, and improve the overall economic strength of the country. For the study of nonlinear systems, neural networks have unique advantages, especially BP neural networks, which can train, learn and predict complex data. In this paper, BP neural network is used to establish the BP neural network model of the Shanghai and Shenzhen 300 Index. The opening price, the highest price and the lowest price of the Shanghai and Shenzhen 300 Index are used as input variables, and the closing price is taken as the output variable to study and predict the closing of the Shanghai and Shenzhen 300 Index. Through the model results, it is found that the BP neural network model can better simulate the Shanghai and Shenzhen 300 Index and achieve the effect of predicting the Shanghai and Shenzhen 300 Index. Applying BP neural network model to nonlinear estimation of the Shanghai and Shenzhen 300 Index, solving nonlinear problems, can promote the healthy development of China’s stock market.
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Liu, H., Ge, N., Zhao, B., Wang, Yh., Xia, F. (2021). Prediction of Shanghai and Shenzhen 300 Index Based on BP Neural Network. In: Liu, Q., Liu, X., Shen, T., Qiu, X. (eds) The 10th International Conference on Computer Engineering and Networks. CENet 2020. Advances in Intelligent Systems and Computing, vol 1274. Springer, Singapore. https://doi.org/10.1007/978-981-15-8462-6_4
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DOI: https://doi.org/10.1007/978-981-15-8462-6_4
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