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Modelling the convenience yield in carbon prices using daily and realized measures

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  • Julien Chevallier

    () (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

This article investigates the modelling of the convenience yield in the European carbon market by using daily and intradaily measures of volatility. The convenience yield stems from differences in spot and futures prices, and can explain why firms hold inventories. The main findings are that (i) a simple AR(4) process best describes the 2008 convenience yield, and (ii) there exists a non linear relation between spot and futures prices. The approach developed in this article captures 74% of the explanatory power for the 2008 convenience yield variable in an autoregressive framework, with carbon spot price levels, moving averages and carbon futures realized volatility measures as exogenous regressors. These results are of interest for energy utilities, risk-managers, and traders exposed to the variation of carbon prices.

Suggested Citation

  • Julien Chevallier, 2010. "Modelling the convenience yield in carbon prices using daily and realized measures," Working Papers halshs-00463921, HAL.
    • Handle: RePEc:hal:wpaper:halshs-00463921
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00463921v2
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    File URL: https://halshs.archives-ouvertes.fr/halshs-00463921v2/document
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    References listed on IDEAS

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    1. Emilie Alberola & Julien Chevallier, 2009. "European Carbon Prices and Banking Restrictions: Evidence from Phase I (2005-2007)," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 51-80.
    2. Geman, Hélyette & Ohana, Steve, 2009. "Forward curves, scarcity and price volatility in oil and natural gas markets," Energy Economics, Elsevier, vol. 31(4), pages 576-585, July.
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    4. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    5. Chevallier, Julien & Ielpo, Florian & Mercier, Ludovic, 2009. "Risk aversion and institutional information disclosure on the European carbon market: A case-study of the 2006 compliance event," Energy Policy, Elsevier, vol. 37(1), pages 15-28, January.
    6. Stronzik, Marcus & Rammerstorfer, Margarethe & Neumann, Anne, 2009. "Does the European natural gas market pass the competitive benchmark of the theory of storage? Indirect tests for three major trading points," Energy Policy, Elsevier, vol. 37(12), pages 5432-5439, December.
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    8. Zhou, Bin, 1996. "High-Frequency Data and Volatility in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 45-52, January.
    9. Chiou Wei, Song Zan & Zhu, Zhen, 2006. "Commodity convenience yield and risk premium determination: The case of the U.S. natural gas market," Energy Economics, Elsevier, vol. 28(4), pages 523-534, July.
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    14. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    15. Chevallier, Julien, 2009. "Carbon futures and macroeconomic risk factors: A view from the EU ETS," Energy Economics, Elsevier, vol. 31(4), pages 614-625, July.
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    18. Szymon Borak & Wolfgang Härdle & Stefan Trück & Rafal Weron, 2006. "Convenience Yields for CO2 Emission Allowance Futures Contracts," SFB 649 Discussion Papers SFB649DP2006-076, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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    Keywords

    Convenience Yield; Carbon Price; EU ETS; High frequency Data; Realized Volatility;

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