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Usefulness of artificial neural networks for early warning system of economic crisis |
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| Authors: | Tae Yoon Kim Kyong Joo Oh Insuk Sohn Changha Hwang |
| Affiliation: | aDepartment of Statistics, Keimyung University, Daegu 704-701, South Korea bDivision of Business Administration, Hansung University, 389, 3-Ga, Samsun-Dong, Sungbuk-Gu, Seoul 136-792, South Korea cDepartment of Statistics, Korea University, Seoul 136-701, South Korea dDepartment of Statistical Information, Catholic University of Daegu, Daegu 713-702, South Korea |
| Abstract: | 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. |
| Keywords: | Economic crisis Early warning system Artificial neural networks Data mining classifier |
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