Forecasting the future earnings of listed companies based on multiuser constraints is the focus of investors, securities dealers, creditors, and management. Some empirical studies at home and abroad indicate that the financial reports issued by listed companies regularly contain information about future changes in earnings. On this basis, this article uses the Bayesian dynamic regression model to predict the changes in the future earnings of listed companies and compares the results with traditional analysis models. Through case analysis, it can be seen that the prediction effect of the Bayesian dynamic regression model is generally better than that of the traditional regression model. The Bayesian model can better predict the results, and through the prediction results, it can also establish an evolutionary game model of the industrial innovation replication dynamic system, which can assist enterprises in making profit decisions.

中文翻译：

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基于多用户需求约束的电子商务经济动态数据评估模型

基于多用户约束来预测上市公司的未来收益是投资者，证券交易商，债权人和管理层的重点。国内外的一些经验研究表明，上市公司发布的财务报告定期包含有关未来收益变化的信息。在此基础上，本文使用贝叶斯动态回归模型预测上市公司未来收益的变化，并将结果与​​传统分析模型进行比较。通过案例分析可以看出，贝叶斯动态回归模型的预测效果总体上优于传统回归模型。贝叶斯模型可以更好地预测结果，并且通过预测结果，