Journal of Information Technology Applications and Management

Korea Data Strategy Society (한국데이터전략학회)
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Development and Application of Risk Recovery Index using Machine Learning Algorithms

기계학습알고리즘을 이용한 위험회복지수의 개발과 활용

  • Kim, Sun Woong (Graduate School of Business Information Technology, Kookmin University)
  • Received : 2016.08.01
  • Accepted : 2016.09.19
  • Published : 2016.12.31
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Abstract

Asset prices decline sharply and stock markets collapse when financial crisis happens. Recently we have encountered more frequent financial crises than ever. 1998 currency crisis and 2008 global financial crisis triggered academic researches on early warning systems that aim to detect the symptom of financial crisis in advance. This study proposes a risk recovery index for detection of good opportunities from financial market instability. We use SVM classifier algorithms to separate recovery period from unstable financial market data. Input variables are KOSPI index and V-KOSPI200 index. Our SVM algorithms show highly accurate forecasting results on testing data as well as training data. Risk recovery index is derived from our SVM-trained outputs. We develop a trading system that utilizes the suggested risk recovery index. The trading result records very high profit, that is, its annual return runs to 121%.

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References

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