Paper Analysis of the Influence Mechanism of Company Stock Price Based on SR-RBF Neural Network

To study the correlation between the stock prices and financial indicators of listed companies in China, this paper selects relevant data represented by the wind database for research. This paper selects 12 financial indicators as the input layer to reflect the company's solvency, profitability, and management capabilities. Based on the SR (Stepwise Regression) algorithm, data dimensionality reduction has become five indicators; the SR-RBF neural network is constructed to train the neural network to obtain the company's stock price simulation. The results show that the model has good robust performance, and the stock price fitting accuracy is 94%. Among them, the most important contribution of net cash flow per share to the stock price reached 45.81, which provides some suggestions for analysing stock price forecasts.