Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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An intelligent early warning system for forecasting abnormal investment trends of foreign investors

외국인 투자자의 비정상적 중·장기매도성향패턴예측을 위한 지능형 조기경보시스템 구축

  • Oh, Kyong Joo (Department of Information and Industrial Engineering, Yonsei University) ;
  • Kim, Young Min (Department of Information and Industrial Engineering, Yonsei University)
  • 오경주 (연세대학교 정보산업공학과) ;
  • 김영민 (연세대학교 정보산업공학과)
  • Received : 2012.11.20
  • Accepted : 2013.01.28
  • Published : 2013.03.31
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Abstract

At local emerging stock markets such as Korea, Hong Kong, Singapore and Taiwan, foreign investors (FI) are recognized as important investment community due to the globalization and deregulation of financial markets. Therefore, it is required to monitor the behavior of FI against a sudden enormous selling stocks for the concerned local governments or private and institutional investors. The main aim of this study is to propose an early warning system (EWS) which purposes issuing a warning signal against the possible massive selling stocks of FI at the market. For this, we suggest machine learning algorithm which predicts the behavior of FI by forecasting future conditions. This study is empirically done for the Korean stock market.

본 연구는 외국인 투자자의 대량매도구간을 서포트 벡터 머신 알고리즘을 통해 모형을 구축하여 발생 가능한 대량매도기간을 사전에 방지할 수 있는 지능형 조기경보시스템을 구축하였다. 이러한 방법은 기존의 Son 등 (2009), Ahn 등 (2011)이 제시한 방법을 토대로 지능형 조기경보시스템에 대한 예측성과를 개선시켰으며, 더 나아가 최근까지 예측성과를 살펴봄으로써 조기경보시스템의 역할을 수행할 수 있는지를 살펴보았다. 또한 구축된 EWSFI는 국내주식시장뿐만 아니라 환율 및 원유시장 등 다양한 경제 분야에서 활용될 수 있는 가능성을 시사하고 있으며, 시장상황의 위기를 사전에 예측하여 예상되는 충격을 줄일 수 있을 것이다.

Keywords

References

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