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Quadratic GARCH Models: Introduction and Applications

이차형식 변동성 Q-GARCH 모형의 비교연구

  • Park, Jin-A (Department of Statistics, Sookmyung Women's University) ;
  • Choi, Moon-Sun (Department of Statistics, Sookmyung Women's University) ;
  • Hwan, Sun-Young (Department of Statistics, Sookmyung Women's University)
  • 박진아 (숙명여자대학교 통계학과) ;
  • 최문선 (숙명여자대학교 통계학과) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Received : 20101000
  • Accepted : 20101200
  • Published : 2011.02.28

Abstract

In GARCH context, the conditional variance (or volatility) is of a quadratic function of the observation process. Examine standard ARCH/GARCH and their variant models in terms of quadratic formulations and it is interesting to note that most models in GARCH context have contained neither the first order term nor the interaction term. In this paper, we consider three models possessing the first order and/or interaction terms in the formulation of conditional variances, viz., quadratic GARCH, absolute value GARCH and bilinear GARCH processes. These models are investigated with a view to model comparisons and applications to financial time series in Korea

Acknowledgement

Supported by : 한국연구재단

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Cited by

  1. Asymmetric CCC Modelling in Multivariate-GARCH with Illustrations of Multivariate Financial Data vol.24, pp.5, 2011, https://doi.org/10.5351/KJAS.2011.24.5.821