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A Common Shock Model for multidimensional electricity intraday price modelling with application to battery valuation

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  • Thomas Deschatre
  • Xavier Warin

Abstract

In this paper, we propose a multidimensional statistical model of intraday electricity prices at the scale of the trading session, which allows all products to be simulated simultaneously. This model, based on Poisson measures and inspired by the Common Shock Poisson Model, reproduces the Samuelson effect (intensity and volatility increases as time to maturity decreases). It also reproduces the price correlation structure, highlighted here in the data, which decreases as two maturities move apart. This model has only three parameters that can be estimated using a moment method that we propose here. We demonstrate the usefulness of the model on a case of storage valuation by dynamic programming over a trading session.

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  • Thomas Deschatre & Xavier Warin, 2023. "A Common Shock Model for multidimensional electricity intraday price modelling with application to battery valuation," Papers 2307.16619, arXiv.org.
  • Handle: RePEc:arx:papers:2307.16619
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    References listed on IDEAS

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    1. Bertrand Tavin & Lorenz Schneider, 2018. "From the Samuelson volatility effect to a Samuelson correlation effect : An analysis of crude oil calendar spread options," Post-Print hal-02311970, HAL.
    2. Schneider, Lorenz & Tavin, Bertrand, 2018. "From the Samuelson volatility effect to a Samuelson correlation effect: An analysis of crude oil calendar spread options," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 185-202.
    3. Kramer, Anke & Kiesel, Rüdiger, 2021. "Exogenous factors for order arrivals on the intraday electricity market," Energy Economics, Elsevier, vol. 97(C).
    4. Kiesel, Rüdiger & Paraschiv, Florentina, 2017. "Econometric analysis of 15-minute intraday electricity prices," Energy Economics, Elsevier, vol. 64(C), pages 77-90.
    5. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    6. Xavier Warin, 2021. "Reservoir optimization and Machine Learning methods," Papers 2106.08097, arXiv.org, revised May 2023.
    7. René Aid & Andrea Cosso & Huyên Pham, 2022. "Equilibrium price in intraday electricity markets," Mathematical Finance, Wiley Blackwell, vol. 32(2), pages 517-554, April.
    8. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2013. "Modelling microstructure noise with mutually exciting point processes," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 65-77, January.
    9. 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).
    10. Emmanuel Bacry & Sylvain Delattre & Marc Hoffmann & Jean-François Muzy, 2013. "Modelling microstructure noise with mutually exciting point processes," Post-Print hal-01313995, HAL.
    11. Jaeck, Edouard & Lautier, Delphine, 2016. "Volatility in electricity derivative markets: The Samuelson effect revisited," Energy Economics, Elsevier, vol. 59(C), pages 300-313.
    12. 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.
    13. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    14. 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.
    15. Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.
    16. Clara Balardy, 2022. "An Empirical Analysis of the Bid-ask Spread in the Continuous Intraday Trading of the German Power Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    17. Edouard Jaeck & Delphine Lautier, 2016. "Volatility in electricity derivative markets: the Samuelson effect revisited," Post-Print hal-01488127, HAL.
    18. Marc Abeille & Bruno Bouchard & Lorenzo Croissant, 2023. "Diffusive Limit Approximation of Pure-Jump Optimal Stochastic Control Problems," Journal of Optimization Theory and Applications, Springer, vol. 196(1), pages 147-176, January.
    19. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    20. Olivier Bardou & Sandrine Bouthemy & Gilles Pages, 2009. "Optimal Quantization for the Pricing of Swing Options," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(2), pages 183-217.
    21. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
    22. Nikolaus Graf von Luckner & Rüdiger Kiesel, 2021. "Modeling Market Order Arrivals on the German Intraday Electricity Market with the Hawkes Process," JRFM, MDPI, vol. 14(4), pages 1-31, April.
    23. Lindskog, Filip & McNeil, Alexander J., 2003. "Common Poisson Shock Models: Applications to Insurance and Credit Risk Modelling," ASTIN Bulletin, Cambridge University Press, vol. 33(2), pages 209-238, November.
    24. Benjamin Favetto, 2019. "The European intraday electricity market : a modeling based on the Hawkes process," Working Papers hal-02089289, HAL.
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    Cited by:

    1. Philippe Bergault & Enzo Cogn'eville, 2024. "Simulating and analyzing a sparse order book: an application to intraday electricity markets," Papers 2410.06839, arXiv.org.

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