IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v32y2010i5p1074-1081.html
   My bibliography  Save this article

A long-term/short-term model for daily electricity prices with dynamic volatility

Author

Listed:
  • Schlueter, Stephan

Abstract

In this paper we introduce a new stochastic long-term/short-term model for short-term electricity prices, and apply it to four major European indices, namely to the German, Dutch, UK and Nordic one. We give evidence that all time series contain certain periodic (mostly annual) patterns, and show how to use the wavelet transform, a tool of multiresolution analysis, for filtering purpose. The wavelet transform is also applied to separate the long-term trend from the short-term oscillation in the seasonal-adjusted log-prices. In all time series we find evidence for dynamic volatility, which we incorporate by using a bivariate GARCH model with constant correlation. Eventually we fit various models from the existing literature to the data, and come to the conclusion that our approach performs best. For the error distribution, the Normal Inverse Gaussian distribution shows the best fit.

Suggested Citation

  • Schlueter, Stephan, 2010. "A long-term/short-term model for daily electricity prices with dynamic volatility," Energy Economics, Elsevier, vol. 32(5), pages 1074-1081, September.
    • Handle: RePEc:eee:eneeco:v:32:y:2010:i:5:p:1074-1081
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(10)00104-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    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. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    4. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    5. M. T. Barlow, 2002. "A Diffusion Model For Electricity Prices," Mathematical Finance, Wiley Blackwell, vol. 12(4), pages 287-298, October.
    6. Apostolos Serletis & Akbar Shahmoradi, 2007. "Measuring and Testing Natural Gas and Electricity Markets Volatility: Evidence from Alberta's Deregulated Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 16, pages 205-220, World Scientific Publishing Co. Pte. Ltd..
    7. Fred Espen Benth & Jan Kallsen & Thilo Meyer-Brandis, 2007. "A Non-Gaussian Ornstein-Uhlenbeck Process for Electricity Spot Price Modeling and Derivatives Pricing," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(2), pages 153-169.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
    10. Makridakis, Spyros, 1993. "Accuracy measures: theoretical and practical concerns," International Journal of Forecasting, Elsevier, vol. 9(4), pages 527-529, December.
    11. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hartner, Michael & Permoser, Andreas, 2018. "Through the valley: The impact of PV penetration levels on price volatility and resulting revenues for storage plants," Renewable Energy, Elsevier, vol. 115(C), pages 1184-1195.
    2. Katarzyna Maciejowska & Rafal Weron, 2013. "Forecasting of daily electricity spot prices by incorporating intra-day relationships: Evidence form the UK power market," HSC Research Reports HSC/13/01, Hugo Steinhaus Center, Wroclaw University of Technology, revised 15 Apr 2013.
    3. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    4. Radu Porumb & Petru Postolache & George Serițan & Ramona Vatu & Oana Ceaki, 2013. "Load profiles analysis for electricity market," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 1(2), pages 30-38, December.
    5. Yan, Guan & Trück, Stefan, 2020. "A dynamic network analysis of spot electricity prices in the Australian national electricity market," Energy Economics, Elsevier, vol. 92(C).
    6. Đurišić, Željko & Mikulović, Jovan & Babić, Iva, 2012. "Impact of wind speed variations on wind farm economy in the open market conditions," Renewable Energy, Elsevier, vol. 46(C), pages 289-296.
    7. Angus, A. & Casado, M. Rivas & Fitzsimons, D., 2012. "Exploring the usefulness of a simple linear regression model for understanding price movements of selected recycled materials in the UK," Resources, Conservation & Recycling, Elsevier, vol. 60(C), pages 10-19.
    8. Semmler, Willi & Di Bartolomeo, Giovanni & Minooei Fard, Behnaz & Braga, Joao Paulo, 2022. "Limit pricing and entry game of renewable energy firms into the energy sector," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 179-190.
    9. Erdogdu, Erkan, 2016. "Asymmetric volatility in European day-ahead power markets: A comparative microeconomic analysis," Energy Economics, Elsevier, vol. 56(C), pages 398-409.
    10. Weron, Rafał & Zator, Michał, 2015. "A note on using the Hodrick–Prescott filter in electricity markets," Energy Economics, Elsevier, vol. 48(C), pages 1-6.
    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. Bobinaite Viktorija & Zuters Jānis, 2016. "Modelling Electricity Price Expectations in a Day-Ahead Market: A Case of Latvia," Economics and Business, Sciendo, vol. 29(1), pages 12-26, August.
    13. Lisi, Francesco & Nan, Fany, 2014. "Component estimation for electricity prices: Procedures and comparisons," Energy Economics, Elsevier, vol. 44(C), pages 143-159.
    14. Katarzyna Maciejowska & Rafał Weron, 2015. "Forecasting of daily electricity prices with factor models: utilizing intra-day and inter-zone relationships," Computational Statistics, Springer, vol. 30(3), pages 805-819, September.
    15. Xu, Weijun & Sun, Qi & Xiao, Weilin, 2012. "A new energy model to capture the behavior of energy price processes," Economic Modelling, Elsevier, vol. 29(5), pages 1585-1591.
    16. Jakub Nowotarski & Jakub Tomczyk & Rafal Weron, 2013. "Modeling and forecasting of the long-term seasonal component of the EEX and Nord Pool spot prices," HSC Research Reports HSC/13/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    17. Katarzyna Maciejowska & Rafal Weron, 2015. "Short- and mid-term forecasting of baseload electricity prices in the UK: The impact of intra-day price relationships and market fundamentals," HSC Research Reports HSC/15/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    18. Sun, Qi & Xu, Weijun & Xiao, Weilin, 2013. "An empirical estimation for mean-reverting coal prices with long memory," Economic Modelling, Elsevier, vol. 33(C), pages 174-181.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Paraschiv, Florentina, 2013. "Price Dynamics in Electricity Markets," Working Papers on Finance 1314, University of St. Gallen, School of Finance.
    3. Le Pen, Yannick & Sévi, Benoît, 2010. "Volatility transmission and volatility impulse response functions in European electricity forward markets," Energy Economics, Elsevier, vol. 32(4), pages 758-770, July.
    4. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    5. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601, December.
    6. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien de Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.
    7. Godin, Frédéric & Ibrahim, Zinatu, 2021. "An analysis of electricity congestion price patterns in North America," Energy Economics, Elsevier, vol. 102(C).
    8. T M Christensen & A. S. Hurn & K A Lindsay, 2008. "Discrete time-series models when counts are unobservable," NCER Working Paper Series 35, National Centre for Econometric Research.
    9. 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, September.
    10. Nomikos, Nikos & Andriosopoulos, Kostas, 2012. "Modelling energy spot prices: Empirical evidence from NYMEX," Energy Economics, Elsevier, vol. 34(4), pages 1153-1169.
    11. Fiuza de Bragança, Gabriel Godofredo & Daglish, Toby, 2016. "Can market power in the electricity spot market translate into market power in the hedge market?," Energy Economics, Elsevier, vol. 58(C), pages 11-26.
    12. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
    13. Suripto & Supriyanto, 2021. "The Effect of the COVID-19 Pandemic on Stock Prices with the Event Window Approach: A Case Study of State Gas Companies, in the Energy Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 155-162.
    14. Tseng, Chih-Hsiung & Cheng, Sheng-Tzong & Wang, Yi-Hsien & Peng, Jin-Tang, 2008. "Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3192-3200.
    15. Aur'elien Alfonsi & Nerea Vadillo, 2023. "Risk valuation of quanto derivatives on temperature and electricity," Papers 2310.07692, arXiv.org, revised Apr 2024.
    16. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    17. Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
    18. Amin Aminimehr & Ali Raoofi & Akbar Aminimehr & Amirhossein Aminimehr, 2022. "A Comprehensive Study of Market Prediction from Efficient Market Hypothesis up to Late Intelligent Market Prediction Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 781-815, August.
    19. Themistoclis Pantos & Stathis Polyzos & Aggelos Armenatzoglou & Ilias Kampouris, 2019. "Volatility Spillovers in Electricity Markets: Evidence from the United States," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 131-143.
    20. de Braganca, Gabriel Fiuza & Daglish, Toby, 2012. "Can market power in the electricity spot market translate into market power in the hedge market?," Working Paper Series 4130, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:32:y:2010:i:5:p:1074-1081. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.