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Functional ARCH analysis for a choice of time interval in intraday return via multivariate volatility

함수형 ARCH 분석 및 다변량 변동성을 통한 일중 로그 수익률 시간 간격 선택

  • Kim, D.H. (Department of Statistics, Sookmyung Women's University) ;
  • Yoon, J.E. (Department of Statistics, Sookmyung Women's University) ;
  • Hwang, S.Y. (Department of Statistics, Sookmyung Women's University)
  • 김다희 (숙명여자대학교 통계학과) ;
  • 윤재은 (숙명여자대학교 통계학과) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Received : 2020.02.04
  • Accepted : 2020.04.01
  • Published : 2020.06.30

Abstract

We focus on the functional autoregressive conditional heteroscedasticity (fARCH) modelling to analyze intraday volatilities based on high frequency financial time series. Multivariate volatility models are investigated to approximate fARCH(1). A formula of multi-step ahead volatilities for fARCH(1) model is derived. As an application, in implementing fARCH(1), a choice of appropriate time interval for the intraday return is discussed. High frequency KOSPI data analysis is conducted to illustrate the main contributions of the article.

본 논문에서는 고빈도 함수적 ARCH 모형을 소개하고 근사모형으로써 다변량 변동성 모형을 고려하였다. 이를 기반으로 함수형 변동성 분석에서 중요한 요소인 일중 로그 수익률의 적절한 시간 간격을 찾아보았다. 또한 함수적 ARCH 모형에서 l-시차 후 변동성 예측식을 제시하고 고빈도 KOSPI 자료에 적합하여 예시하였다.

Keywords

References

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