SHS Web Conf.
Volume 151, 20223rd International Symposium on Economics, Management, and Sustainable Development (EMSD 2022)
|Number of page(s)
|16 December 2022
Stock Prediction and Analysis based on RNN Neural Network
Division of General Studies, University of Illinois Urbana-Champaign, Champaign, United States
The greater the investment, the greater the risk, and building a stock prediction model with high accuracy is of great theoretical significance and practical application for financial investors. It has become a trend to apply artificial neural network to stock prediction. In this paper, we select the Shanghai Composite Index to predict and analyze the stock price. A three-layer neural network is built and the convergence rate is analyzed, and it is obtained that the fitting effect will be more accurate when the selected data is reasonable and has good properties, and finally the change of the stock in a short period of time is obtained. The neural network is feasible and reasonable for stock price prediction, which in turn helps to improve the profitability of stockholders.
Key words: Stock analysis / neural network / RNN
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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