A method for forecasting of stock price based on deep learning

Forecasting stock prices is of great significance for investors to reduce risks and make more intelligent investment decisions. Aiming at the problem of stock price prediction, this paper proposes a stock price prediction model based on deep neural network. The experimental results show that the proposed model effectively improves the accuracy of stock price prediction, and can help investors and market participants make more intelligent investment decisions, optimize investment portfolios, and reduce financial risks. In addition, the self-learning adaptive ability of the deep neural network enables the model to maintain a high predictive function in the ever-changing market environment, providing a reliable reference for investors.