基于BP神经网络和面板数据的上市公司财务危机预警

Research on Financial Warning for Listed Companies by Using BP Neural Networks and Panel Data

在作者前期研究的基础上引入面板数据,以T-2、T-3期财务数据组合的面板数据(panel data)作为研究样本,构建BP神经网络模型对上市公司的财务状况进行预测.实验表明,1)使用面板数据进行的BP神经网络预警分析显示出稳定、连续的预测性能,这正好适合构建具有实际应用价值的中长期预警模型,使模型具有广泛的实践应用价值;2)模型提前3年和4年的预测能力分别为88.46%和75.64%,较之以往同行的研究及作者前期的研究精度均有较大的提高.

On the basis of the authors＇ previous research and with the introduction of panel data, this paper constructed a BP neural networks model to predict the financial status of listed companies, by taking panel data composed of the financial data of T-2 and T-3 as the sample.The research indicates that： 1） with panel data,the BP neural networks warning analysis is of stable and continuous predictability, which is suitable in constructing practical mid-term and long-erm prediction models to make the model more applicable; 2） the predictability precision is 88.46% and 75.64% for T-3 and T-4,respectively,superior to that of counterparts and the previous research.