Analysis and Research on the Stock Volatility Factors of Chinese Listed Companies Based on the FA-ANN-MLP Model

Abstract

Accounting information is an essential basis for investors to make decisions, and it is vital to analyze the impact of accounting information on stock prices accurately. Therefore, this article establishes Factor Analysis-Artificial Neural Network-Radial Basis Function (FA-ANN-MLP) model, through empirical analysis of Sinopec Group’s stock prices and accounting information, to explore accounting information indicators that significantly affect stock prices and Predict the trend of stock price rise and fall. The results show that the accuracy of the model’s prediction is 81.7%, and profitability and earnings per share are significant factors that affect stock prices. This model has a high accuracy rate in predicting stock price rise and fall, providing investors with a theoretical basis.