基于FA-ANN-MLP模型的中国上市公司股票波动因素分析与研究

Jingqi Liu, Xinzhen Pei, Junyan Zou
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引用次数: 0

摘要

会计信息是投资者进行决策的重要依据,准确分析会计信息对股票价格的影响至关重要。因此,本文建立因子分析-人工神经网络-径向基函数(FA-ANN-MLP)模型,通过对中国石化集团股价与会计信息的实证分析,探索显著影响股价的会计信息指标,预测股价涨跌趋势。结果表明,该模型的预测准确率为81.7%,盈利能力和每股收益是影响股价的显著因素。该模型预测股价涨跌的准确率较高,为投资者提供了理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and Research on the Stock Volatility Factors of Chinese Listed Companies Based on the FA-ANN-MLP Model
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.
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