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Predicting the Prices of Electricity Derivatives on the Energy Exchange

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  • Štěpán Kratochvíl
  • Oldřich Starý

Abstract

There is a need to focus on electricity derivative trading, because this is an important and expanding field. The aim of this paper is long-term forecasting of the daily futures prices. Two approaches were used for this, namely the use of spot price forecasting to model the future prices and forecasting future prices directly. We will show on an EEX case study that better results can be achieved by the first approach, where we use mean-reverting, jump-diffusion and regime-switching models for spot price forecasting. The best results of spot price forecasting are achieved by the jump-diffusion model, where we will present the benefit of the use of filtered calibration data.

Suggested Citation

  • Štěpán Kratochvíl & Oldřich Starý, 2013. "Predicting the Prices of Electricity Derivatives on the Energy Exchange," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2013(6), pages 65-81.
    • Handle: RePEc:prg:jnlaop:v:2013:y:2013:i:6:id:421:p:65-81
    DOI: 10.18267/j.aop.421
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    References listed on IDEAS

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    1. Huisman, Ronald & Huurman, Christian & Mahieu, Ronald, 2007. "Hourly electricity prices in day-ahead markets," Energy Economics, Elsevier, vol. 29(2), pages 240-248, March.
    2. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    3. Viehmann, Johannes, 2011. "Risk premiums in the German day-ahead Electricity Market," Energy Policy, Elsevier, vol. 39(1), pages 386-394, January.
    4. Deng, S.J. & Oren, S.S., 2006. "Electricity derivatives and risk management," Energy, Elsevier, vol. 31(6), pages 940-953.
    5. Thilo Meyer-Brandis & Peter Tankov, 2008. "Multi-Factor Jump-Diffusion Models Of Electricity Prices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(05), pages 503-528.
    6. Jan Seifert & Marliese Uhrig-Homburg, 2007. "Modelling jumps in electricity prices: theory and empirical evidence," Review of Derivatives Research, Springer, vol. 10(1), pages 59-85, January.
    7. Joanna Janczura & Rafał Weron, 2012. "Efficient estimation of Markov regime-switching models: An application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 385-407, July.
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    More about this item

    Keywords

    electricity derivatives; energy exchange; predicting prices; estimation of the parameters; data filtering;
    All these keywords.

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • G1 - Financial Economics - - General Financial Markets
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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