Application of BP Neural Networks in Stock Price Prediction

With the rapid development of the modern economy and the rise of investment awareness among people, stock investment has become an essential part of life. Currently, BP Neural Networks (BPNN) are considered capable of contributing to stock price prediction, and establishing a stock market prediction model with high accuracy has significant practical value for investors. This paper explores the factors influencing stock prices and discusses the feasibility of using BP Neural Networks to analyze and predict stock trends. By using 40 sample data points from AAPL as the training sample for quantitative calculations, the results indicate that using BP Neural Networks for short-term prediction is feasible.