응용통계연구 (The Korean Journal of Applied Statistics)

  • 제27권7호
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  • Pages.1139-1149
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  • 2014
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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정준상관분석을 통한 다변량 금융시계열의 변동성 분석

Multivariate Volatility Analysis via Canonical Correlations for Financial Time Series

  • 이승연 (숙명여자대학교 통계학과) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Lee, Seung Yeon (Department of Statistics, Sookmyung Women's University) ;
  • Hwang, S.Y. (Department of Statistics, Sookmyung Women's University)
  • 투고 : 2014.11.16
  • 심사 : 2014.11.23
  • 발행 : 2014.12.31
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⟨ 이전 논문 다음 논문 ⟩

초록

다변량 금융시계열의 변동성분석을 다변량 기법인 정준상관분석(canonocal correaltion analysis)을 이용해 분석하였다. 변동성의 특성상 계수들이 비음(non-negative)인 정준상관분석, 즉, non-negative and sparse canonical correlation analysis (NSCCA)를 이용해 보았다. 본 논문은 다변량 시계열의 변동성 커브에 대해 연구하고 있으며 제시된 방법론을 이변량 주식자료분석을 통해 예시해 보았다.

Multivariate volatility is summarized through canonical correlation analysis (CCA). Along with the standard CCA, non-negative and sparse canonical correlation analysis (NSCCA) is introduced to make sure that volatility coefficients are non-negative and the number of coefficients in the volatility CCA is as small as possible. Various multivariate financial time series are analyzed to illustrate the main contribution of the paper.

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참고문헌

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