IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i22p7531-d676816.html
   My bibliography  Save this article

Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market

Author

Listed:
  • Rainer Baule

    (Chair of Banking and Finance, University of Hagen, Universitätsstraße 41, 58084 Hagen, Germany)

  • Michael Naumann

    (Chair of Banking and Finance, University of Hagen, Universitätsstraße 41, 58084 Hagen, Germany)

Abstract

Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted R 2 of 0.479 for volatility and around 0.3 for the dispersion measures.

Suggested Citation

  • Rainer Baule & Michael Naumann, 2021. "Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market," Energies, MDPI, vol. 14(22), pages 1-24, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:22:p:7531-:d:676816
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/22/7531/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/22/7531/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1533-1547.
    2. Angelica Gianfreda, 2010. "Volatility and Volume Effects in European Electricity Spot Markets," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 39(1‐2), pages 47-63, February.
    3. Marcel Kremer & Rüdiger Kiesel & Florentina Paraschiv, 2020. "Intraday Electricity Pricing of Night Contracts," Energies, MDPI, vol. 13(17), pages 1-14, September.
    4. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    5. Christopher Kath, 2019. "Modeling Intraday Markets under the New Advances of the Cross-Border Intraday Project (XBID): Evidence from the German Intraday Market," Energies, MDPI, vol. 12(22), pages 1-35, November.
    6. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    7. Scharff, Richard & Amelin, Mikael, 2016. "Trading behaviour on the continuous intraday market Elbas," Energy Policy, Elsevier, vol. 88(C), pages 544-557.
    8. Pape, Christian, 2018. "The impact of intraday markets on the market value of flexibility — Decomposing effects on profile and the imbalance costs," Energy Economics, Elsevier, vol. 76(C), pages 186-201.
    9. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    10. Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
    11. Tim Janke & Florian Steinke, 2019. "Forecasting the Price Distribution of Continuous Intraday Electricity Trading," Energies, MDPI, vol. 12(22), pages 1-14, November.
    12. Kramer, Anke & Kiesel, Rüdiger, 2021. "Exogenous factors for order arrivals on the intraday electricity market," Energy Economics, Elsevier, vol. 97(C).
    13. 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.
    14. Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
    15. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
    16. repec:bla:ecnote:v:39:y:2010:i:s1:p:47-63 is not listed on IDEAS
    17. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    18. Weber, Christoph, 2010. "Adequate intraday market design to enable the integration of wind energy into the European power systems," Energy Policy, Elsevier, vol. 38(7), pages 3155-3163, July.
    19. Clò, Stefano & Cataldi, Alessandra & Zoppoli, Pietro, 2015. "The merit-order effect in the Italian power market: The impact of solar and wind generation on national wholesale electricity prices," Energy Policy, Elsevier, vol. 77(C), pages 79-88.
    20. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
    21. Maciejowska, Katarzyna & Nitka, Weronika & Weron, Tomasz, 2021. "Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices," Energy Economics, Elsevier, vol. 99(C).
    22. Paschen, Marius, 2016. "Dynamic analysis of the German day-ahead electricity spot market," Energy Economics, Elsevier, vol. 59(C), pages 118-128.
    23. Gürtler, Marc & Paulsen, Thomas, 2018. "The effect of wind and solar power forecasts on day-ahead and intraday electricity prices in Germany," Energy Economics, Elsevier, vol. 75(C), pages 150-162.
    24. 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.
    25. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    26. François Benhmad & Jacques Percebois, 2016. "Wind power feed-in impact on electricity prices in Germany 2009-2013," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 81-96, June.
    27. Kath, Christopher & Ziel, Florian, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Energy Economics, Elsevier, vol. 76(C), pages 411-423.
    28. Zachmann, Georg, 2008. "Electricity wholesale market prices in Europe: Convergence?," Energy Economics, Elsevier, vol. 30(4), pages 1659-1671, July.
    29. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Contract durations in the electricity market: Causal impact of 15min trading on the EPEX SPOT market," Energy Economics, Elsevier, vol. 69(C), pages 367-378.
    30. Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2017. "Modeling and forecasting realized volatility in German–Austrian continuous intraday electricity prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 680-690, September.
    31. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2017. "Does renewable energy generation decrease the volatility of electricity prices? An analysis of Denmark and Germany," Energy Economics, Elsevier, vol. 62(C), pages 270-282.
    32. Pape, Christian & Hagemann, Simon & Weber, Christoph, 2016. "Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market," Energy Economics, Elsevier, vol. 54(C), pages 376-387.
    33. Sergei Kulakov and Florian Ziel, 2021. "The Impact of Renewable Energy Forecasts on Intraday Electricity Prices," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    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. Anne Carolina Rodrigues Klaar & Stefano Frizzo Stefenon & Laio Oriel Seman & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2023. "Structure Optimization of Ensemble Learning Methods and Seasonal Decomposition Approaches to Energy Price Forecasting in Latin America: A Case Study about Mexico," Energies, MDPI, vol. 16(7), pages 1-17, March.
    2. Simon Hirsch & Florian Ziel, 2022. "Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution," Papers 2211.13002, arXiv.org.
    3. Christoph Graf & Thomas Kuppelwieser & David Wozabal, 2024. "Frequent Auctions for Intraday Electricity Markets," The Energy Journal, , vol. 45(1), pages 231-256, January.
    4. Rainer Baule & Michael Naumann, 2022. "Flexible Short-Term Electricity Certificates—An Analysis of Trading Strategies on the Continuous Intraday Market," Energies, MDPI, vol. 15(17), pages 1-28, August.

    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. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    2. Christopher Kath & Florian Ziel, 2020. "Optimal Order Execution in Intraday Markets: Minimizing Costs in Trade Trajectories," Papers 2009.07892, arXiv.org, revised Oct 2020.
    3. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    4. Katarzyna Maciejowska, 2022. "A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets," Papers 2205.00975, arXiv.org.
    5. Li, Wei & Paraschiv, Florentina, 2022. "Modelling the evolution of wind and solar power infeed forecasts," Journal of Commodity Markets, Elsevier, vol. 25(C).
    6. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    9. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
    10. Narajewski, Michał & Ziel, Florian, 2022. "Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs," Energy Economics, Elsevier, vol. 110(C).
    11. Rainer Baule & Michael Naumann, 2022. "Flexible Short-Term Electricity Certificates—An Analysis of Trading Strategies on the Continuous Intraday Market," Energies, MDPI, vol. 15(17), pages 1-28, August.
    12. Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
    13. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    14. Micha{l} Narajewski & Florian Ziel, 2021. "Optimal bidding in hourly and quarter-hourly electricity price auctions: trading large volumes of power with market impact and transaction costs," Papers 2104.14204, arXiv.org, revised Feb 2022.
    15. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
    16. Hakan Acaroğlu & Fausto Pedro García Márquez, 2021. "Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy," Energies, MDPI, vol. 14(22), pages 1-23, November.
    17. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    18. 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.
    19. Marcel Kremer & Rüdiger Kiesel & Florentina Paraschiv, 2020. "Intraday Electricity Pricing of Night Contracts," Energies, MDPI, vol. 13(17), pages 1-14, September.
    20. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.

    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:gam:jeners:v:14:y:2021:i:22:p:7531-:d:676816. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.