Usefulness of artificial neural networks for early warning system of economic crisis

被引:46
作者
Kim, TY
Oh, KJ
Sohn, I
Hwang, CH
机构
[1] Hansung Univ, Div Business Adm, Seoul 136792, South Korea
[2] Keimyung Univ, Dept Stat, Taegu 704701, South Korea
[3] Korea Univ, Dept Stat, Seoul 136701, South Korea
[4] Catholic Univ, Dept Stat Informat, Taegu 713702, South Korea
关键词
economic crisis; early warning system; artificial neural networks; data mining classifier;
D O I
10.1016/j.eswa.2003.12.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
During the 1990s, the economic crises in many parts of the world have sparked a need in building early warning system (EWS) which produces signal for possible crisis, and accordingly various EWSs have been established. In this paper, we focus on an interesting issue: 'How to train EWS?' To study this, various aspects of the training data (i.e. the past crisis related data) will be discussed and then several data mining classifiers including artificial neural networks (ANN) will be probed as a training tool for EWS. To emphasize empirical side of the problem, EWS for Korean economy is to be constructed. Our investigation suggests that ANN may be quite competitive in building EWS over other data mining classifiers. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:583 / 590
页数:8
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