An Investigation on the BP Neural Network Model for Predicting the Stock Value of Alibaba

With the development of society, people's living standards have continued to improve. At the same time, residents' disposable income has also increased. As a result, the stock market, characterized by high returns, has become favored by investors. However, numerous factors in society can affect stock price fluctuations, causing significant losses to both investors and companies. This paper focuses on the stock market of the internet industry, specifically taking Alibaba as a case study. It selects both systematic and non-systematic risks that influence stock prices as factors of consideration and employs BP neural networks to investigate the impact of each factor on internet industry stocks. By collecting data and establishing a predictive model, this study aims to provide a reference for investment decisions, thereby helping to mitigate risks and reduce losses.