Using neural networks to support early warning system for financial crisis forecasting

Kyong Joo Oh, Tae Yoon Kim, Hyoung Yong Lee, Hakbae Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This study deals with the construction process of a daily financial condition indicator (DFCI), which can be used as an early warning signal using neural networks and nonlinear programming. One of the characteristics in the proposed indicator is to establish an alarm zone in the DFCI, which plays a role of predicting a potential financial crisis. The previous financial condition indicators based on statistical methods are developed such that they examine whether a crisis will be break out within 24 months. In this study, however, the alarm zone makes it possible for the DFCI to forecast an unexpected crisis on a daily basis and then issue an early warning signal. Therefore, DFCI involves daily monitoring of the evolution of the stock price index, foreign exchange rate and interest rate, which tend to exhibit unusual behaviors preceding a possible crisis. Using nonlinear programming, the procedure of DFCI construction is completed by integrating three sub-DFCIs, based on each financial variable, into the final DFCI. The DFCI for Korean financial market will be established as an empirical study. This study then examines the predictability of alarm zone for the financial crisis forecasting in Korea.

Original languageEnglish
Title of host publicationAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings
Pages284-296
Number of pages13
DOIs
Publication statusPublished - 2005 Dec 1
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 2005 Dec 52005 Dec 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
CountryAustralia
CitySydney
Period05/12/505/12/9

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Oh, K. J., Kim, T. Y., Lee, H. Y., & Lee, H. (2005). Using neural networks to support early warning system for financial crisis forecasting. In AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings (pp. 284-296). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI). https://doi.org/10.1007/11589990_31