摘要
本文采用三种多元统计分析及人工智能方法分别对我国上市公司财务困境预测进行了实证研究,建立了四种预测模型。判定结果表明,该四种方法都可以用来进行财务困境预测,但判定效果是有差异的,Logistic模型是最有效的一种方法。
In this paper, three multivariate analysis method and artificial intelligence method are applied to make a positive study of the forecast research about financial distress in China's listed corporations , and four forecasting models are established. The result of the discrimination shows that all theses four methods can be used in forecasting the financial distress, but the effects are different , of which the effect of logistic model is the best.
出处
《现代财经（天津财经大学学报）》
CSSCI
2004年第5期57-60,共4页
Modern Finance and Economics：Journal of Tianjin University of Finance and Economics
关键词
财务困境
判别分析
主成分分析
LOGISTIC模型
BP神经网络
Financial Distress
Discriminating Analysis
Principal Component Analysis
Logistic Regressive Model
BP Neural Network
