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

Tae Yoon Kim, Kyong Joo Oh, Insuk Sohn, Changha Hwang

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)583-590
Number of pages8
JournalExpert Systems with Applications
Issue number4
Publication statusPublished - 2004 May

Bibliographical note

Funding Information:
This research is supported by Korea Research Foundation Grant 2003-070-C00008.

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence


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