• Title/Summary/Keyword: 코퓰러

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Performance analysis of EVT-GARCH-Copula models for estimating portfolio Value at Risk (포트폴리오 VaR 측정을 위한 EVT-GARCH-코퓰러 모형의 성과분석)

  • Lee, Sang Hun;Yeo, Sung Chil
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.753-771
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    • 2016
  • Value at Risk (VaR) is widely used as an important tool for risk management of financial institutions. In this paper we discuss estimation and back testing for VaR of the portfolio composed of KOSPI, Dow Jones, Shanghai, Nikkei indexes. The copula functions are adopted to construct the multivariate distributions of portfolio components from marginal distributions that combine extreme value theory and GARCH models. Volatility models with t distribution of the error terms using Gaussian, t, Clayton and Frank copula functions are shown to be more appropriate than the other models, in particular the model using the Frank copula is shown to be the best.

Estimation and Performance Analysis of Risk Measures using Copula and Extreme Value Theory (코퓰러과 극단치이론을 이용한 위험척도의 추정 및 성과분석)

  • Yeo, Sung-Chil
    • The Korean Journal of Applied Statistics
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    • v.19 no.3
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    • pp.481-504
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    • 2006
  • VaR, a tail-related risk measure is now widely used as a tool for a measurement and a management of financial risks. For more accurate measurement of VaR, recently we are particularly concerned about the approach based on extreme value theory rather than the traditional method based on the assumption of normal distribution. However, many studies about the approaches using extreme value theory was done only for the univariate case. In this paper, we discuss portfolio risk measurements with modelling multivariate extreme value distributions by combining copulas and extreme value theory. We also discuss the estimation of ES together with VaR as portfolio risk measures. Finally, we investigate the relative superiority of EVT-copula approach than variance-covariance method through the back-testing of an empirical data.

Probabilistic evaluation of ecological drought in forest areas using satellite remote sensing data (인공위성 원격 감지 자료를 활용한 산림지역의 생태학적 가뭄 가능성에 대한 확률론적 평가)

  • Won, Jeongeun;Seo, Jiyu;Kang, Shin-Uk;Kim, Sangdan
    • Journal of Korea Water Resources Association
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    • v.54 no.9
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    • pp.705-718
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    • 2021
  • Climate change has a significant impact on vegetation growth and terrestrial ecosystems. In this study, the possibility of ecological drought was investigated using satellite remote sensing data. First, the Vegetation Health Index was estimated from the Normalized Difference Vegetation Index and Land Surface Temperature provided by MODIS. Then, a joint probability model was constructed to estimate the possibility of vegetation-related drought in various precipitation/evaporation scenarios in forest areas around 60 major ASOS sites of the Meteorological Administration located throughout Korea. The results of this study show the risk pattern of drought related to forest vegetation under conditions of low atmospheric moisture supply or high atmospheric moisture demand. It also identifies the sensitivity of drought risks associated with forest vegetation under various meterological drought conditions. These findings provide insights for decision makers to assess drought risk and develop drought mitigation strategies related to forest vegetation in a warming era.