Stock Prediction and Analysis based on RNN Neural Network

Abstract

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.