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Price Dynamics in Electricity Markets

In: Handbook of Risk Management in Energy Production and Trading

Author

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  • Florentina Paraschiv

    (University of St. Gallen)

Abstract

With the liberalization of global power markets, modeling of exchange-traded electricity contracts has attracted significantly the attention of both academic and industry. In this paper we offer an overview of the most common deseasonalization techniques and modeling approaches in the literature. We extract the deterministic component of EEX Phelix hourly electricity prices and we discuss different financial and time-series models for their stochastic component. Additionally we apply extreme value theory (EVT) to investigate the tails of the price changes distribution. Generally our results suggest EVT to be of interest to both risk managers and portfolio managers in the highly volatile electricity markets.

Suggested Citation

  • Florentina Paraschiv, 2013. "Price Dynamics in Electricity Markets," International Series in Operations Research & Management Science, in: Raimund M. Kovacevic & Georg Ch. Pflug & Maria Teresa Vespucci (ed.), Handbook of Risk Management in Energy Production and Trading, edition 127, chapter 0, pages 47-69, Springer.
    • Handle: RePEc:spr:isochp:978-1-4614-9035-7_3
    DOI: 10.1007/978-1-4614-9035-7_3
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    Citations

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    Cited by:

    1. Karl Frauendorfer & Florentina Paraschiv & Michael Schürle, 2018. "Cross-Border Effects on Swiss Electricity Prices in the Light of the Energy Transition," Energies, MDPI, vol. 11(9), pages 1-30, August.
    2. Morales, Lucía & Hanly, Jim, 2018. "European power markets–A journey towards efficiency," Energy Policy, Elsevier, vol. 116(C), pages 78-85.
    3. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    4. Giorgia Callegaro & Andrea Mazzoran & Carlo Sgarra, 2019. "A Self-Exciting Modelling Framework for Forward Prices in Power Markets," Papers 1910.13286, arXiv.org.
    5. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
    6. Benth, Fred Espen & Paraschiv, Florentina, 2018. "A space-time random field model for electricity forward prices," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 203-216.
    7. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
    8. Amal Abdel Razzac & Linda Salahaldin & Salah Eddine Elayoubi & Yezekael Hayel & Tijani Chahed, 2017. "A Game Theoretical Real Options Framework for Investment Decisions in Mobile TV Infrastructure," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-34, August.
    9. Keles, Dogan & Scelle, Jonathan & Paraschiv, Florentina & Fichtner, Wolf, 2016. "Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks," Applied Energy, Elsevier, vol. 162(C), pages 218-230.
    10. Mangirdas Morkunas & Gintaras Cernius & Gintare Giriuniene, 2019. "Assessing Business Risks of Natural Gas Trading Companies: Evidence from GET Baltic," Energies, MDPI, vol. 12(14), pages 1-14, July.

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