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Modeling Volatility and Dependence of European Carbon and Energy Prices

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  • Jonathan Berrisch
  • Sven Pappert
  • Florian Ziel
  • Antonia Arsova

Abstract

We study the prices of European Emission Allowances (EUA), whereby we analyze their uncertainty and dependencies on related energy prices (natural gas, coal, and oil). We propose a probabilistic multivariate conditional time series model with a VECM-Copula-GARCH structure which exploits key characteristics of the data. Data are normalized with respect to inflation and carbon emissions to allow for proper cross-series evaluation. The forecasting performance is evaluated in an extensive rolling-window forecasting study, covering eight years out-of-sample. We discuss our findings for both levels- and log-transformed data, focusing on time-varying correlations, and in view of the Russian invasion of Ukraine.

Suggested Citation

  • Jonathan Berrisch & Sven Pappert & Florian Ziel & Antonia Arsova, 2022. "Modeling Volatility and Dependence of European Carbon and Energy Prices," Papers 2208.14311, arXiv.org, revised Feb 2023.
    • Handle: RePEc:arx:papers:2208.14311
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    References listed on IDEAS

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    Cited by:

    1. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    2. Paul Ghelasi & Florian Ziel, 2024. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Papers 2406.00326, arXiv.org, revised Aug 2024.
    3. Sikorska-Pastuszka, Magdalena & Papież, Monika, 2023. "Dynamic volatility connectedness in the European electricity market," Energy Economics, Elsevier, vol. 127(PA).

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