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Analytical Approximation for the Price Dynamics of Spark Spread Options

Author

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  • Benth Fred E

    (University of Oslo, Norway)

  • Saltyte-Benth Jurate

    (Faculty of Medicine, University of Oslo and Helse Øst Health Services Research Centre, Akershus University Hospital, Norway)

Abstract

This paper presents an analytic approximation for the pricing dynamics of spark spread options in terms of Fourier transforms. We propose to model the spark spread, that is, the price difference of electricity and gas, directly using a mean-reverting model with diffusion and jumps. The model is analyzed empirically, and shown to fit observed data in the UK reasonably well. The main advantage with the model is that the spark spread of electricity and gas forwards, being forwards with delivery over periods, can be priced analytically. The price dynamics for different spark spread options with electricity and gas forwards as underlying, is analytically derived through Fourier transforms. These pricing expressions allow for efficient numerical valuations via the fast Fourier transform technique.

Suggested Citation

  • Benth Fred E & Saltyte-Benth Jurate, 2006. "Analytical Approximation for the Price Dynamics of Spark Spread Options," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-28, September.
    • Handle: RePEc:bpj:sndecm:v:10:y:2006:i:3:n:8
    DOI: 10.2202/1558-3708.1355
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    References listed on IDEAS

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    1. 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.
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    Citations

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    Cited by:

    1. 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, August.
    2. Cartea, Álvaro & González-Pedraz, Carlos, 2012. "How much should we pay for interconnecting electricity markets? A real options approach," Energy Economics, Elsevier, vol. 34(1), pages 14-30.
    3. 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).
    4. Cartea, Álvaro & Jaimungal, Sebastian & Qin, Zhen, 2019. "Speculative trading of electricity contracts in interconnected locations," Energy Economics, Elsevier, vol. 79(C), pages 3-20.
    5. Wobben, Magnus & Dieckmann, Birgit & Reichmann, Oleg, 2012. "Valuation of physical transmission rights—An analysis of electricity cross-border capacities between Germany and the Netherlands," Energy Policy, Elsevier, vol. 42(C), pages 174-180.
    6. Fasen, Vicky, 2013. "Statistical estimation of multivariate Ornstein–Uhlenbeck processes and applications to co-integration," Journal of Econometrics, Elsevier, vol. 172(2), pages 325-337.
    7. Kevin W. Lu, 2022. "Calibration for multivariate Lévy-driven Ornstein-Uhlenbeck processes with applications to weak subordination," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 365-396, July.
    8. Farshid Mehrdoust & Idin Noorani, 2023. "Valuation of Spark-Spread Option Written on Electricity and Gas Forward Contracts Under Two-Factor Models with Non-Gaussian Lévy Processes," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 807-853, February.

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