The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Multivariate volatility for high-frequency financial series

다변량 고빈도 금융시계열의 변동성 분석

  • Lee, G.J. (Department of Statistics, Sookmyung Women's University) ;
  • Hwang, Sun Young (Department of Statistics, Sookmyung Women's University)
  • 이근주 (숙명여자대학교 통계학과) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Received : 2016.12.23
  • Accepted : 2017.01.18
  • Published : 2017.02.28
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Abstract

Multivariate GARCH models are interested in conditional variances (volatilities) as well as conditional correlations between return time series. This paper is concerned with high-frequency multivariate financial time series from which realized volatilities and realized conditional correlations of intra-day returns are calculated. Existing multivariate GARCH models are reviewed comparatively with the realized volatility via canonical correlations and value at risk (VaR). Korean stock prices are analysed for illustration.

본 논문은 다변량 변동성을 다루고 있다. 최근 들어 활발하게 연구가 되고 있는 고빈도(high frequency)자료에 기초한 변동성 측정방법인 실현변동성을 계산하고 기존의 다변량 GARCH 모형과 비교분석하였다. 정준상관분석과 VaR분석을 이용하여 실현변동성과 다양한 다변량 GARCH 모형을 비교하였으며 최근 6년 동안의 삼성전자/현대차 거래 가격 고빈도 데이터를 이용하여 실증분석을 실시하였다.

Keywords

References

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