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Liquidity costs on intraday power markets: Continuous trading versus auctions

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  • Kuppelwieser, Thomas
  • Wozabal, David

Abstract

We analyze liquidity costs on continuous and auction-based intraday power markets using a cost-of-round-trip measure that works for both market designs. We use data from the Italian auction-based intraday market and the German continuous market and present descriptive statistics as well as multivariate regression models to analyze determinants of liquidity costs in both markets. To test for differences in liquidity due to market design, we employ a double machine learning technique controlling for several confounding variables. We show that weekly patterns, yearly seasonality, electricity demand, as well as the influence of temperatures significantly affect liquidity costs. Comparing liquidity costs in both market, we find that, overall, liquidity costs are lower on the Italian market. However, Italian costs increase towards later auctions, while the costs on the German continuous intraday market decrease and reach their low close to physical delivery, where costs are lower than on the last Italian market trading the corresponding products.

Suggested Citation

  • Kuppelwieser, Thomas & Wozabal, David, 2021. "Liquidity costs on intraday power markets: Continuous trading versus auctions," Energy Policy, Elsevier, vol. 154(C).
  • Handle: RePEc:eee:enepol:v:154:y:2021:i:c:s0301421521001683
    DOI: 10.1016/j.enpol.2021.112299
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    1. Simon Hagemann & Christoph Weber, 2013. "An Empirical Analysis of Liquidity and its Determinants in The German Intraday Market for Electricity," EWL Working Papers 1317, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2013.
    2. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    3. Graf, Christoph & Wozabal, David, 2013. "Measuring competitiveness of the EPEX spot market for electricity," Energy Policy, Elsevier, vol. 62(C), pages 948-958.
    4. Karsten Neuhoff & Nolan Ritter & Aymen Salah-Abou-El-Enien & Philippe Vassilopoulos, 2016. "Intraday Markets for Power: Discretizing the Continuous Trading," Cambridge Working Papers in Economics 1616, Faculty of Economics, University of Cambridge.
    5. Raimund Kovacevic & David Wozabal, 2014. "A semiparametric model for electricity spot prices," IISE Transactions, Taylor & Francis Journals, vol. 46(4), pages 344-356.
    6. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    7. Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
    8. Tim Janke & Florian Steinke, 2019. "Forecasting the Price Distribution of Continuous Intraday Electricity Trading," Energies, MDPI, vol. 12(22), pages 1-14, November.
    9. 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.
    10. Simon Hagemann & Christoph Weber, 2015. "Trading Volumes in Intraday Markets - Theoretical Reference Model and Empirical Observations in Selected European Markets," EWL Working Papers 1503, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Apr 2015.
    11. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    12. 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.
    13. Bartosz Uniejewski & Rafał Weron, 2018. "Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models," Energies, MDPI, vol. 11(8), pages 1-26, August.
    14. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
    15. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    16. 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.
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    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.

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