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Short-term European Union Allowance price forecasting with artificial neural networks

Author

Listed:
  • Agustín García

    (University of Extremadura, Spain)

  • Agustín García

    (Tufts University, United States)

  • Miguel A. Jaramillo-Morán

    (University of Extremadura, Spain)

Abstract

The European Union Emissions Trading Scheme (EU ETS) was created to reduce greenhouse gas emissions. Companies producing carbon emissions have to manage associated cash flows by buying or selling carbon allowances. Moreover, future carbon prices could affect company decision making on decarbonization technology investments. In this paper, we forecasted short-term future carbon allowance prices using an artificial intelligence tool: a neural network. The resulting mean error was 1.7617 %. This is indicative of very good performance for a time series whose evolution is influenced by subjective economic and political decisions. The inclusion in the forecasting model of variables possibly directly related to the evolution of the price of CO2 emission allowances did not improve prediction accuracy. Therefore, we can assume that emission allowances evolve following a random path. The neural network provided reliable predictions which agents selling or buying allowances can use to make their decisions.

Suggested Citation

  • Agustín García & Agustín García & Miguel A. Jaramillo-Morán, 2020. "Short-term European Union Allowance price forecasting with artificial neural networks," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(1), pages 261-275, September.
    • Handle: RePEc:ssi:jouesi:v:8:y:2020:i:1:p:261-275
    DOI: 10.9770/jesi.2020.8.1(18)
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    References listed on IDEAS

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    Cited by:

    1. Jonathan Berrisch & Florian Ziel, 2021. "CRPS Learning," Papers 2102.00968, arXiv.org, revised Nov 2021.
    2. Berrisch, Jonathan & Pappert, Sven & Ziel, Florian & Arsova, Antonia, 2023. "Modeling volatility and dependence of European carbon and energy prices," Finance Research Letters, Elsevier, vol. 52(C).

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    More about this item

    Keywords

    European Union Allowances (EUA); carbon allowance price; neural networks; time series forecasting;
    All these keywords.

    JEL classification:

    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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