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Forecasting volatility of carbon under EU ETS: a multi-phase study

Author

Listed:
  • Ajay K. Dhamija

    (Defence Research and Development Organisation (DRDO))

  • Surendra S. Yadav

    (Indian Institute Technology (IIT))

  • PK Jain

    (Indian Institute Technology (IIT))

Abstract

Carbon management is a strategic priority and organizations need to forecast carbon for that. We aim to find out the best ARIMA-GARCH model for forecasting conditional return and volatility of European Union Allowance (EUA) for all three phases of European Union Emissions Trading Scheme and the Rolled Over series. We use European Climate Exchange Dec 2007, Dec 2012, Dec 2015 expiry and the Rolled Over Dec 2015 expiry future contracts of EUA. The previous studies in this area have focused on a particular subset of EUA data and do not take care of the multicollinearities. We take EUA data from all three phases and the Rolled Over series, adopt principal component analysis to eliminate multicollinearities and then fit GARCH models for comprehensive analysis. The study establishes that the best models for predicting EUA phase I, II, III and Rolled Over series are asymmetric GARCH models.

Suggested Citation

  • Ajay K. Dhamija & Surendra S. Yadav & PK Jain, 2017. "Forecasting volatility of carbon under EU ETS: a multi-phase study," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(2), pages 299-335, April.
    • Handle: RePEc:spr:envpol:v:19:y:2017:i:2:d:10.1007_s10018-016-0155-4
    DOI: 10.1007/s10018-016-0155-4
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    Cited by:

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    3. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    4. Po Yun & Chen Zhang & Yaqi Wu & Yu Yang, 2022. "Forecasting Carbon Dioxide Price Using a Time-Varying High-Order Moment Hybrid Model of NAGARCHSK and Gated Recurrent Unit Network," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
    5. Yang Liu & Xueqing Yang & Mei Wang, 2021. "Global Transmission of Returns among Financial, Traditional Energy, Renewable Energy and Carbon Markets: New Evidence," Energies, MDPI, vol. 14(21), pages 1-32, November.
    6. Wen Zhang & Zhibin Wu, 2022. "Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 615-632, April.

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