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Pricing of Swing Options in a Mean Reverting Model with Jumps

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  • Mats Kjaer

Abstract

We investigate the pricing of swing options in a model where the logarithm of the spot price is the sum of a deterministic seasonal trend and an Ornstein-Uhlenbeck process driven by a jump diffusion. First we calibrate the model to Nord Pool electricity market data. Second, the existence of an optimal exercise strategy is proved, and we present a numerical algorithm for computation of the swing option prices. It involves dynamic programming and the solution of multiple parabolic partial integro-differential equations by finite differences. Numerical results show that adding jumps to a diffusion may result in 2-35% higher swing option prices, depending on the moneyness and timing flexibility of the option.

Suggested Citation

  • Mats Kjaer, 2008. "Pricing of Swing Options in a Mean Reverting Model with Jumps," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(5-6), pages 479-502.
    • Handle: RePEc:taf:apmtfi:v:15:y:2008:i:5-6:p:479-502
    DOI: 10.1080/13504860802170556
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    Citations

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    Cited by:

    1. Marcus Eriksson & Jukka Lempa & Trygve Nilssen, 2014. "Swing options in commodity markets: a multidimensional Lévy diffusion model," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(1), pages 31-67, February.
    2. Anna Maria Gambaro & Nicola Secomandi, 2021. "A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 47-67, January.
    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. Piergiacomo Sabino, 2021. "Normal Tempered Stable Processes and the Pricing of Energy Derivatives," Papers 2105.03071, arXiv.org.
    5. 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.
    6. Cummins, Mark & Kiely, Greg & Murphy, Bernard, 2018. "Gas storage valuation under multifactor Lévy processes," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 167-184.
    7. Seiji Harikae & James S. Dyer & Tianyang Wang, 2021. "Valuing Real Options in the Volatile Real World," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 171-189, January.
    8. J. Lars Kirkby & Shi-Jie Deng, 2019. "Swing Option Pricing By Dynamic Programming With B-Spline Density Projection," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(08), pages 1-53, December.
    9. Nicola Cufaro Petroni & Piergiacomo Sabino, 2019. "Fast Pricing of Energy Derivatives with Mean-reverting Jump-diffusion Processes," Papers 1908.03137, arXiv.org, revised Mar 2020.
    10. Nicola Cufaro Petroni & Piergiacomo Sabino, 2020. "Gamma Related Ornstein-Uhlenbeck Processes and their Simulation," Papers 2003.08810, arXiv.org.
    11. Piergiacomo Sabino, 2020. "Exact Simulation of Variance Gamma related OU processes: Application to the Pricing of Energy Derivatives," Papers 2004.06786, arXiv.org.

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