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Variance risk-premia in CO2 markets

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  • Chevallier, Julien

Abstract

This paper proposes a new methodology to measure the volatility of CO2 assets computed as the difference between model-free implied volatility (from option prices) and model-free realized volatility (from high-frequency intraday data), coined as ‘variance risk-premia’ (Carr and Wu, 2009; Bollerslev et al., 2009; Trolle and Schwartz, 2010), during 2008–2011. We find that variance risk-premia are equal to a daily sample average of 0.79 for European Union Allowances and 0.18 for Certified Emissions Reductions. In the spirit of the CAPM, we show that the beta can only explain a small portion, and that macro risk factors specific to CO2 markets and energy volatilities can improve this result. Hence, there exists a systematic variance risk factor in CO2 markets that asks for a highly risk premium. Further analysis shows that variance risk-premia are time-varying, and can be used as strong predictors for forecasting CO2 returns.

Suggested Citation

  • Chevallier, Julien, 2013. "Variance risk-premia in CO2 markets," Economic Modelling, Elsevier, vol. 31(C), pages 598-605.
  • Handle: RePEc:eee:ecmode:v:31:y:2013:i:c:p:598-605
    DOI: 10.1016/j.econmod.2012.12.017
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    Cited by:

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    2. 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.
    3. Tietjen, Oliver & Lessmann, Kai & Pahle, Michael, 2021. "Hedging and temporal permit issuances in cap-and-trade programs: The Market Stability Reserve under risk aversion," Resource and Energy Economics, Elsevier, vol. 63(C).
    4. Pedro Antonio Martín-Cervantes & María del Carmen Valls Martínez, 2023. "Unraveling the relationship between betas and ESG scores through the Random Forests methodology," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-29, September.
    5. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    6. 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.
    7. Friedrich, Marina & Mauer, Eva-Maria & Pahle, Michael & Tietjen, Oliver, 2020. "From fundamentals to financial assets: the evolution of understanding price formation in the EU ETS," EconStor Preprints 196150, ZBW - Leibniz Information Centre for Economics, revised 2020.
    8. Yue-Jun Zhang, 2016. "Research on carbon emission trading mechanisms: current status and future possibilities," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 39(1/2), pages 89-107.
    9. Getachew Nigatu, 2016. "Assessing the effects of climate change policy on the volatility of carbon prices in reference to the Great Recession," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(2), pages 200-215, July.

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    More about this item

    Keywords

    Variance risk-premia; CO2 market; Model-free implied volatility; Realized volatility; Forecasting; EUA; CER; EU ETS; CDM; Energy volatilities;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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