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Factor models in the German electricity market: Stylized facts, seasonality, and calibration

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  • Hinderks, W.J.
  • Wagner, A.

Abstract

The class of arithmetic factor models is flexible enough to model all stylized facts occurring in electricity markets, including negative prices, while still yielding tractable derivative prices. In this paper we conduct a thorough review of the requirements and possibilities of factor models. We compare different seasonality functions and study their power to deseasonalise day-ahead spot prices from the EPEX Germany/Austria market. Furthermore, we introduce an alternative method to estimate mean reversion speed based on ARMA time series and a method to evaluate the distributional fit of the model to realised market prices, which we apply to two non-Gaussian estimated models.

Suggested Citation

  • Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
  • Handle: RePEc:eee:eneeco:v:85:y:2020:i:c:s0140988319301033
    DOI: 10.1016/j.eneco.2019.03.024
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    1. Lars Ivar Hagfors & Hilde Hørthe Kamperud & Florentina Paraschiv & Marcel Prokopczuk & Alma Sator & Sjur Westgaard, 2016. "Prediction of extreme price occurrences in the German day-ahead electricity market," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1929-1948, December.
    2. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    3. 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.
    4. Gonzalez, Jhonny & Moriarty, John & Palczewski, Jan, 2017. "Bayesian calibration and number of jump components in electricity spot price models," Energy Economics, Elsevier, vol. 65(C), pages 375-388.
    5. Helyette Geman & A. Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," Post-Print halshs-00144198, HAL.
    6. Iivo Vehvilainen, 2002. "Basics of electricity derivative pricing in competitive markets," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 45-60.
    7. Ketterer, Janina C., 2014. "The impact of wind power generation on the electricity price in Germany," Energy Economics, Elsevier, vol. 44(C), pages 270-280.
    8. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811, January.
    9. Benhmad, François & Percebois, Jacques, 2018. "Photovoltaic and wind power feed-in impact on electricity prices: The case of Germany," Energy Policy, Elsevier, vol. 119(C), pages 317-326.
    10. Erik Gawel & Klaas Korte & Kerstin Tews, 2015. "Distributional Challenges of Sustainability Policies—The Case of the German Energy Transition," Sustainability, MDPI, vol. 7(12), pages 1-17, December.
    11. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    12. Caldana, Ruggero & Fusai, Gianluca & Roncoroni, Andrea, 2017. "Electricity forward curves with thin granularity: Theory and empirical evidence in the hourly EPEXspot market," European Journal of Operational Research, Elsevier, vol. 261(2), pages 715-734.
    13. repec:dau:papers:123456789/607 is not listed on IDEAS
    14. Ben Hambly & Sam Howison & Tino Kluge, 2009. "Modelling spikes and pricing swing options in electricity markets," Quantitative Finance, Taylor & Francis Journals, vol. 9(8), pages 937-949.
    15. Zipp, Alexander, 2017. "The marketability of variable renewable energy in liberalized electricity markets – An empirical analysis," Renewable Energy, Elsevier, vol. 113(C), pages 1111-1121.
    16. Bennedsen, Mikkel, 2017. "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, vol. 63(C), pages 301-313.
    17. Villaplana Conde, Pablo, 2003. "Pricing power derivatives: a two-factor jump-diffusion approach," DEE - Working Papers. Business Economics. WB wb031805, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    18. Higgs, Helen & Worthington, Andrew, 2008. "Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: The Australian wholesale spot electricity market," Energy Economics, Elsevier, vol. 30(6), pages 3172-3185, November.
    19. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    20. Janczura, Joanna & Trück, Stefan & Weron, Rafał & Wolff, Rodney C., 2013. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," Energy Economics, Elsevier, vol. 38(C), pages 96-110.
    21. Wolfe, Stephen James, 1982. "On a continuous analogue of the stochastic difference equation Xn=[rho]Xn-1+Bn," Stochastic Processes and their Applications, Elsevier, vol. 12(3), pages 301-312, May.
    22. Benth, Fred Espen & Kiesel, Rüdiger & Nazarova, Anna, 2012. "A critical empirical study of three electricity spot price models," Energy Economics, Elsevier, vol. 34(5), pages 1589-1616.
    23. François Benhmad & Jacques Percebois, 2018. "Photovoltaic and wind power feed-in impact on electricity prices: The case of Germany," Post-Print hal-01830537, HAL.
    24. Bierbrauer, Michael & Menn, Christian & Rachev, Svetlozar T. & Truck, Stefan, 2007. "Spot and derivative pricing in the EEX power market," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3462-3485, November.
    25. Andreas Wagner, 2014. "Residual Demand Modeling and Application to Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    26. Les Clewlow & Chris Strickland, 1999. "Valuing Energy Options in a One Factor Model Fitted to Forward Prices," Research Paper Series 10, Quantitative Finance Research Centre, University of Technology, Sydney.
    27. Benth, Fred Espen & Klüppelberg, Claudia & Müller, Gernot & Vos, Linda, 2014. "Futures pricing in electricity markets based on stable CARMA spot models," Energy Economics, Elsevier, vol. 44(C), pages 392-406.
    28. Martin Barlow & Yuri Gusev & Manpo Lai, 2004. "Calibration Of Multifactor Models In Electricity Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 101-120.
    29. Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
    30. Juri Hinz & Lutz Von Grafenstein & Michel Verschuere & Martina Wilhelm, 2005. "Pricing electricity risk by interest rate methods," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 49-60.
    31. repec:dau:papers:123456789/1433 is not listed on IDEAS
    32. 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.
    33. Hélyette Geman & Andrea Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1225-1262, May.
    34. Ole E. Barndorff‐Nielsen & Neil Shephard, 2001. "Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 167-241.
    35. Helyette Geman, 2005. "Commodities and Commodity Derivatives. Modeling and Pricing for Agriculturals, Metals and Energy," Post-Print halshs-00144182, HAL.
    36. Ole E. Barndorff-Nielsen, 1997. "Processes of normal inverse Gaussian type," Finance and Stochastics, Springer, vol. 2(1), pages 41-68.
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    Cited by:

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    3. Christian Laudag'e & Florian Aichinger & Sascha Desmettre, 2023. "A Comparative Study of Factor Models for Different Periods of the Electricity Spot Price Market," Papers 2306.07731, arXiv.org, revised Sep 2023.
    4. Andrés Oviedo-Gómez & Sandra Milena Londoño-Hernández & Diego Fernando Manotas-Duque, 2021. "Effects of the COVID-19 Pandemic on the Spot Price of Colombian Electricity," Energies, MDPI, vol. 14(21), pages 1-14, October.
    5. Hugo Algarvio, 2023. "The Economic Sustainability of Variable Renewable Energy Considering the Negotiation of Different Support Schemes," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
    6. Wagner, Andreas & Ramentol, Enislay & Schirra, Florian & Michaeli, Hendrik, 2022. "Short- and long-term forecasting of electricity prices using embedding of calendar information in neural networks," Journal of Commodity Markets, Elsevier, vol. 28(C).
    7. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    8. Maren Diane Schmeck & Stefan Schwerin, 2021. "The Effect of Mean-Reverting Processes in the Pricing of Options in the Energy Market: An Arithmetic Approach," Risks, MDPI, vol. 9(5), pages 1-19, May.

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    More about this item

    Keywords

    Electricity price model; Calibration; Arithmetic factor models; Seasonality functions;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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