Effectiveness of neural networks for prediction of corporate financial distress in China

被引：0

作者：

Xie, JG ^{[1
]}

Wang, J ^{[1
]}

Qiu, ZD ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Inst Sci Informat, Beijing 100044, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 2 | 2004年 / 3174卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The study examines the effectiveness of two types of neural networks in predicting corporate financial distress in China. Back-propagation and LVQ neural networks are considered. The neural networks are compared against Logistic Regression, which is the most popular one among the traditional methods. The results show that the level of Type I and Type 11 errors varies greatly across techniques. The neural networks have low level of Type I error and high level of Type 11 error, while Logistic Regression has the reverse relationship. Since the cost of Type I is more expensive than that of Type 11 error in this field. We demonstrate that the performance of the neural networks tested is superior to Logistic Regression.

引用

页码：994 / 999

页数：6

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