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Measuring Value-at-Risk and Expected Shortfall of crude oil portfolio using extreme value theory and vine copula

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  • Yu, Wenhua
  • Yang, Kun
  • Wei, Yu
  • Lei, Likun

Abstract

Volatilities of crude oil price have important impacts on the steady and sustainable development of world real economy. Thus it is of great academic and practical significance to model and measure the volatility and risk of crude oil markets accurately. This paper aims to measure the Value-at-Risk (VaR) and Expected Shortfall (ES) of a portfolio consists of four crude oil assets by using GARCH-type models, extreme value theory (EVT) and vine copulas. The backtesting results show that the combination of GARCH-type-EVT models and vine copula methods can produce accurate risk measures of the oil portfolio. Mixed R-vine copula is more flexible and superior to other vine copulas. Different GARCH-type models, which can depict the long-memory and/or leverage effect of oil price volatilities, however offer similar marginal distributions of the oil returns.

Suggested Citation

  • Yu, Wenhua & Yang, Kun & Wei, Yu & Lei, Likun, 2018. "Measuring Value-at-Risk and Expected Shortfall of crude oil portfolio using extreme value theory and vine copula," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1423-1433.
    • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:1423-1433
    DOI: 10.1016/j.physa.2017.08.064
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    7. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
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    9. Zou, Yingchao & Yu, Lean & Tso, Geoffrey K.F. & He, Kaijian, 2020. "Risk forecasting in the crude oil market: A multiscale Convolutional Neural Network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
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    12. Hamed Tabasi & Vahidreza Yousefi & Jolanta Tamošaitienė & Foroogh Ghasemi, 2019. "Estimating Conditional Value at Risk in the Tehran Stock Exchange Based on the Extreme Value Theory Using GARCH Models," Administrative Sciences, MDPI, vol. 9(2), pages 1-17, May.
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