The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A Study on Outlier Detection Method for Financial Time Series Data

재무 시계열 자료의 이상치 탐지 기법 연구

  • Ha, M.H. (Department of Statistics, Chung-Ang University) ;
  • Kim, S. (Department of Statistics, Chung-Ang University)
  • Received : 20091200
  • Accepted : 20100100
  • Published : 2010.02.28
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Abstract

In this paper, we show the performance evaluation of outlier detection methods based on the GARCH model. We first introduce GARCH model and the methods of outlier detection in the GARCH model. The results of small simulation and the real KOSPI data show the out-performance of the outlier detection method over the traditional method in the GARCH model.

본 연구에서는 재무 시계열 자료를 분석하는데 있어 유용하게 쓰이는 이분산성 시계열 모형하에서 이상치 탐지 기법을 적용하여 그 효율성을 보이고자 한다. 먼저 GARCH 모형과 GARCH 모형하에서 이상치 탐지 기법에 대해 소개하고, 적용된 방법이 기존의 전통적인 이상치 탐지 방법보다 성능이 우수함을 시뮬레이션과 실제 KOSPI 자료에 적합시켜 입증하였다.

Keywords

References

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