Performance Analysis of Volatility Models for Estimating Portfolio Value at Risk

포트폴리오 VaR 측정을 위한 변동성 모형의 성과분석

  • Yeo, Sung Chil (Department of Applied Statistics, Konkuk University) ;
  • Li, Zhaojing (Department of Applied Statistics, Konkuk University)
  • 여성칠 (건국대학교 응용통계학과) ;
  • 이조청 (건국대학교 응용통계학과)
  • Received : 2015.03.30
  • Accepted : 2015.04.15
  • Published : 2015.06.30


VaR is now widely used as an important tool to evaluate and manage financial risks. In particular, it is important to select an appropriate volatility model for the rate of return of financial assets. In this study, both univariate and multivariate models are considered to evaluate VaR of the portfolio composed of KOSPI, Hang-Seng, Nikkei indexes, and their performances are compared through back testing techniques. Overall, multivariate models are shown to be more appropriate than univariate models to estimate the portfolio VaR, in particular DCC and ADCC models are shown to be more superior than others.


Supported by : 건국대학교


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