Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Saddlepoint approximations for the risk measures of portfolios based on skew-normal risk factors

왜정규 위험요인 기반 포트폴리오 위험측도에 대한 안장점근사

  • Yu, Hye-Kyung (Public Procurement Service) ;
  • Na, Jong-Hwa (Department of Information and Statistics/Business Data Convergence, Chungbuk National University)
  • 유혜경 (조달청) ;
  • 나종화 (충북대학교 정보통계학과/비즈니스데이터융합학과)
  • Received : 2014.07.02
  • Accepted : 2014.08.03
  • Published : 2014.11.30
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Abstract

We considered saddlepoint approximations to VaR (value at risk) and ES (expected shortfall) which frequently encountered in finance and insurance as the measures of risk management. In this paper we supposed univariate and multivariate skew-normal distributions, instead of traditional normal class distributions, as underlying distribution of linear portfolios. Simulation results are provided and showed the suggested saddlepoint approximations are very accurate than normal approximations.

본 논문에서는 금융분야에서 사용되고 있는 포트폴리오 위험측도인 VaR (value at risk)와 ES (expected shortfall)의 측정 방법으로 안장점근사의 적용 방법을 제시하였다. 본 연구의 특징은 금융자료에 대하여 정규분포를 가정하지 않고, 치우침을 가정한 왜정규분포를 가정하여 왜정규분포를 따르는 위험요인으로 구성된 선형 포트폴리오 위험측도에 대해 안장점근사를 실시하였다. 또한 모의실험을 통해 위험측도의 안장점근사의 정도가 매우 우수함을 확인하였다.

Keywords

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