Korean Economic Condition Indicator Using a Neural Network Trained on the 1997 Crisis

by Tae Yoon Kim, Changha Hwang and Jongkyu Lee

Journal of Data Science, v.2, no.4, 371-381

Abstract

The main aim of this article is to develop an efficient indicator for Korean economic conditions based on its disastrous 1997 economic crisis experience. For this an artificial neural network, a well known tool for pattern recognition, is employed. The dynamic movements of the 1997 stock price index are divided into three patterns or intervals according to a "volatility" level and then presented to the neural network as a training set. It turns out that the crisis trained neural network has a surprisingly high degree of accuracy in judging the given economic condition, which strongly suggests that the post crisis Korean economy has been profoundly influenced by the 1997 crisis. This result might also be useful to other countries trying to build an early crisis warning indicator. .

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