The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Extended Constant Conditional Correlation (ECCC) Model for Multivariate GARCH Time Series: an Illustration

다변량 GARCH 모형의 CCC 및 ECCC 비교분석

  • Lee, Seung Yeon (Department of Statistics, Sookmyung Women's University) ;
  • Hwang, S.Y. (Department of Statistics, Sookmyung Women's University)
  • 이승연 (숙명여자대학교 통계학과) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Received : 2014.12.05
  • Accepted : 2014.12.10
  • Published : 2014.12.31
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Abstract

Constant conditional correlation (CCC) is frequently employed for parsimony in the field of multivariate GARCH time series. An extended-CCC (ECCC) model is further developed in order to allow interactions between multivariate volatilities. The paper introduces both CCC model and ECCC model to the domestic financial time series. The CCC and ECCC models are fitted and then compared with each other through various multivatiate time series.

다변량 금융시계열 분석모형인 상수조건부상관(CCC)에 대해 알아보았으며, 개개 변동성간의 상호작용을 함께 고려한 확장된 상수조건부상관(ECCC)을 소개하고 국내 금융시계열에 적용하였다. 다양한 이변량 수익률 자료를 통해 CCC와 ECCC를 비교분석하였다.

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References

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