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Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS

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  • Feng, Zhen-Hua
  • Wei, Yi-Ming
  • Wang, Kai

Abstract

With the rapid growth of the carbon market, carbon price fluctuations are increasingly important for market participants. Carbon market risk directly affects the investor confidence and emission reduction results. In the present study, extreme value theory (EVT) is used to analyze risk exposure for carbon price and to measure the Value at Risk (VaR) for the carbon market. GARCH models are applied to establish a model of price volatility for the spot market and the futures market and to calculate dynamic VaR. Traditional VaR and VaR based on EVT are also compared. The results show that the downside risk is higher than the upside risk for the carbon market. Upside and downside risks are higher in the first phase (June 2005–December 2007) than in the second phase (February 2008–December 2009) for both the spot and futures markets. Upside and downside risks are similar for the spot and futures markets during the same phase. The results also show that the EVT VaR is more effective than the traditional method, which can reduce the risks for market participants. Dynamic VaR based on GARCH and EVT can effectively measure the EU ETS market risk.

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  • Feng, Zhen-Hua & Wei, Yi-Ming & Wang, Kai, 2012. "Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS," Applied Energy, Elsevier, vol. 99(C), pages 97-108.
  • Handle: RePEc:eee:appene:v:99:y:2012:i:c:p:97-108
    DOI: 10.1016/j.apenergy.2012.01.070
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    1. Federico Galán-Valdivieso & Elena Villar-Rubio & María-Dolores Huete-Morales, 2018. "The erratic behaviour of the EU ETS on the path towards consolidation and price stability," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 18(5), pages 689-706, October.
    2. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
    3. Yifei Hua & Feng Dong, 2019. "China’s Carbon Market Development and Carbon Market Connection: A Literature Review," Energies, MDPI, Open Access Journal, vol. 12(9), pages 1-25, May.
    4. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    5. Reboredo, Juan C. & Ugando, Mikel, 2015. "Downside risks in EU carbon and fossil fuel markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 111(C), pages 17-35.
    6. Cummins, Mark, 2013. "EU ETS market interactions: The case for multiple hypothesis testing approaches," Applied Energy, Elsevier, vol. 111(C), pages 701-709.
    7. Jamshidi, Movahed & Kebriaei, Hamed & Sheikh-El-Eslami, Mohammad-Kazem, 2018. "An interval-based stochastic dominance approach for decision making in forward contracts of electricity market," Energy, Elsevier, vol. 158(C), pages 383-395.
    8. Bao-jun Tang & Cheng Shen & Yi-fan Zhao, 2015. "Market risk in carbon market: an empirical analysis of the EUA and sCER," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 333-346, February.
    9. Jianguo Zhou & Xuechao Yu & Xiaolei Yuan, 2018. "Predicting the Carbon Price Sequence in the Shenzhen Emissions Exchange Using a Multiscale Ensemble Forecasting Model Based on Ensemble Empirical Mode Decomposition," Energies, MDPI, Open Access Journal, vol. 11(7), pages 1-17, July.
    10. Shackleton, Ross T. & Angelstam, Per & van der Waal, Benjamin & Elbakidze, Marine, 2017. "Progress made in managing and valuing ecosystem services: a horizon scan of gaps in research, management and governance," Ecosystem Services, Elsevier, vol. 27(PB), pages 232-241.
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    12. Bangzhu Zhu & Shunxin Ye & Kaijian He & Julien Chevallier & Rui Xie, 2019. "Measuring the risk of European carbon market: an empirical mode decomposition-based value at risk approach," Annals of Operations Research, Springer, vol. 281(1), pages 373-395, October.
    13. Jarmila Zimmermannová, 2015. "Pilot Analysis of the Behaviour of Companies Within the 3rd Trading Period of the EU ETS in the Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(6), pages 2213-2220.
    14. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2019. "Quantifying Risk in Traditional Energy and Sustainable Investments," Sustainability, MDPI, Open Access Journal, vol. 11(3), pages 1-22, January.
    15. Urban, Timothy L. & Chiang, Wen-Chyuan, 2016. "Designing energy-efficient serial production lines: The unpaced synchronous line-balancing problem," European Journal of Operational Research, Elsevier, vol. 248(3), pages 789-801.
    16. Crossland, Jarrod & Li, Bin & Roca, Eduardo, 2013. "Is the European Union Emissions Trading Scheme (EU ETS) informationally efficient? Evidence from momentum-based trading strategies," Applied Energy, Elsevier, vol. 109(C), pages 10-23.
    17. Chai, Shanglei & Zhou, P., 2018. "The Minimum-CVaR strategy with semi-parametric estimation in carbon market hedging problems," Energy Economics, Elsevier, vol. 76(C), pages 64-75.

    More about this item

    Keywords

    EU ETS; VaR; GARCH; EVT; Carbon price; Risk measurement;

    JEL classification:

    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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