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초록
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.
키워드
high-frequency time series; realized volatility; multivariate GARCH; 고빈도 자료; 실현변동성; 다변량 GARCH
- 제목
- Multivariate volatility for high-frequency financial series
- 제목 (타언어)
- 다변량 고빈도 금융시계열의 변동성 분석
- 저자
- 이근주; 황선영
- 발행일
- 2017-02
- 저널명
- 응용통계연구
- 권
- 30
- 호
- 1
- 페이지
- 169 ~ 180