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Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study

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  • Janczura, Joanna
  • Wójcik, Edyta

Abstract

The price risk related to trading in electricity markets has increased significantly in the recent years, due to the ongoing markets liberalization and the growing renewable energy sources production. In this paper we propose a short-term risk management strategy for an electricity supplier, that utilizes diversification of the markets for electricity trade. Based on the day-ahead probabilistic forecasts of electricity prices we calculate predictions of different risk and profit measures taking into account a possible split of the traded energy among markets. Strategies aiming at the risk minimization, profit maximization or finding optimal trade-off between risk and return are applied for the German and Polish electricity markets. The obtained results show that diversifying the markets at which electricity is traded leads to higher profits than trading on the day-ahead market and, at the same time, lower risk than associated with trading on the intraday or balancing market. In each of the considered cases, except for volatility as a risk measure for the German market, the goal of the strategy has been achieved. Implementation of the dynamic strategies has improved the outcomes in terms of risk or profit, compared to the static ones.

Suggested Citation

  • Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    • Handle: RePEc:eee:eneeco:v:110:y:2022:i:c:s0140988322001840
    DOI: 10.1016/j.eneco.2022.106015
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    Cited by:

    1. Bartosz Uniejewski, 2023. "Electricity price forecasting with Smoothing Quantile Regression Averaging: Quantifying economic benefits of probabilistic forecasts," Papers 2302.00411, arXiv.org, revised Jan 2024.
    2. Weronika Nitka & Rafał Weron, 2023. "Combining predictive distributions of electricity prices. Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(3), pages 105-118.
    3. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
    4. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).

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    More about this item

    Keywords

    Electricity market; Risk management; Short-term forecasting; Strategy; Intraday market; Balancing market; Germany; Poland;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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