基于朴素贝叶斯算法的*ST企业财务状况预测研究

Research on Financial Situation Prediction of *ST Enterprises Based on Naive Bayesian Algorithm

随着我国经济的迅猛发展,金融市场中*ST企业不断增多。上市企业达到连续三年亏损就会被执行退市预警,这不仅使普通投资者回报下降、也使企业股东权益受损。为了对*ST企业发展状况更好的评价,文章以基于朴素贝叶斯算法的财务状况预测模型分析为研究课题,以沪深A股主板*ST企业t-1和t-2年的财务数据为研究样本,运用混淆矩阵评价指标构建具有适用性的财务状况预测模型。实证结果显示模型具有较好的推广效果与泛化作用,对*ST企业财务状况具备一定的预测效果。

With the rapid development of China's economy,there are more and more*ST enterprises in the financial market.Listed companies will be subject to delisting warning if they lose money for three consecutive years,which not only reduces the return of ordinary investors,but also damages the shareholders'rights and interests.In order to better evaluate the development of*ST enterprises,this paper takes the analysis of financial situation prediction model based on Naive Bayesian algorithm as the research topic,takes the financial data of Shanghai and Shenzhen A-share main board*ST enterprises in T-1 and T-2 years as the research samples,and uses the confusion matrix evaluation index to construct a suitable financial situation prediction model.The empirical results show that the model has a good promotion effect and generalization effect,and has a certain prediction effect on the financial situation of*ST enterprises.