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Modeling Intraday Markets under the New Advances of the Cross-Border Intraday Project (XBID): Evidence from the German Intraday Market

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  • Christopher Kath

    (University of Duisburg-Essen, 45141 Essen, Germany
    Current address: Altenessenerstr. 27, 45141 Essen, Germany.)

Abstract
The intraday cross-border project (XBID) allows intraday market participants to trade based on a shared order book independent of countries or local energy exchanges. This theoretically leads to an efficient allocation of cross-border capacities and ensures maximum market liquidity across European intraday markets. If this postulation holds, the technical implementation of XBID might mark a regime switch in any intraday price series. We present a regression-based model for intraday markets with a particular focus on the German European Power Exchange (EPEX) intraday market and evaluate if the introduction of XBID influence prices, volume or volatility. We analyze partial volume-weighted average prices and standard deviations as well as cross-border volumes at different trading times. We are able to falsify our initial hypothesis assuming a measurable influence of changes caused by XBID. Thus, this paper contributes to the ongoing discussion on appropriate modeling of intraday markets and demonstrates that XBID does not necessarily need to be included in any model.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:22:p:4339-:d:286894
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    References listed on IDEAS

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    Cited by:

    1. Despoina I. Makrygiorgou & Nikos Andriopoulos & Ioannis Georgantas & Christos Dikaiakos & George P. Papaioannou, 2020. "Cross-Border Electricity Trading in Southeast Europe Towards an Internal European Market," Energies, MDPI, vol. 13(24), pages 1-18, December.
    2. Kramer, Anke & Kiesel, Rüdiger, 2021. "Exogenous factors for order arrivals on the intraday electricity market," Energy Economics, Elsevier, vol. 97(C).
    3. 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.
    4. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
    5. Michał Narajewski & Florian Ziel, 2019. "Estimation and Simulation of the Transaction Arrival Process in Intraday Electricity Markets," Energies, MDPI, vol. 12(23), pages 1-16, November.
    6. Christopher Kath & Florian Ziel, 2020. "Optimal Order Execution in Intraday Markets: Minimizing Costs in Trade Trajectories," Papers 2009.07892, arXiv.org, revised Oct 2020.
    7. 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.
    8. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    9. Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
    10. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    11. Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemysław Zaleski & Rafał Weron, 2020. "Balancing Generation from Renewable Energy Sources: Profitability of an Energy Trader," Energies, MDPI, vol. 13(1), pages 1-15, January.
    12. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
    13. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    14. Moritz Nobis & Carlo Schmitt & Ralf Schemm & Armin Schnettler, 2020. "Pan-European CVaR-Constrained Stochastic Unit Commitment in Day-Ahead and Intraday Electricity Markets," Energies, MDPI, vol. 13(9), pages 1-35, May.
    15. 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.
    16. Christos Roumkos & Pandelis Biskas & Ilias Marneris, 2020. "Modeling Framework Simulating the TERRE Activation Optimization Function," Energies, MDPI, vol. 13(11), pages 1-30, June.
    17. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    18. 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.

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