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Optimal exercise of swing contracts in energy markets: an integral constrained stochastic optimal control problem

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  • M. Basei
  • A. Cesaroni
  • T. Vargiolu

Abstract

We characterize the value of swing contracts in continuous time as the unique viscosity solution of a Hamilton-Jacobi-Bellman equation with suitable boundary conditions. The case of contracts with penalties is straightforward, and in that case only a terminal condition is needed. Conversely, the case of contracts with strict constraints gives rise to a stochastic control problem with a nonstandard state constraint. We approach this problem by a penalty method: we consider a general constrained problem and approximate the value function with a sequence of value functions of appropriate unconstrained problems with a penalization term in the objective functional. Coming back to the case of swing contracts with strict constraints, we finally characterize the value function as the unique viscosity solution with polynomial growth of the Hamilton-Jacobi-Bellman equation subject to appropriate boundary conditions.

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  • M. Basei & A. Cesaroni & T. Vargiolu, 2013. "Optimal exercise of swing contracts in energy markets: an integral constrained stochastic optimal control problem," Papers 1307.1320, arXiv.org.
    • Handle: RePEc:arx:papers:1307.1320
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    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. René Carmona & Nizar Touzi, 2008. "Optimal Multiple Stopping And Valuation Of Swing Options," Mathematical Finance, Wiley Blackwell, vol. 18(2), pages 239-268, April.
    3. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    4. Edoli, Enrico & Fiorenzani, Stefano & Ravelli, Samuele & Vargiolu, Tiziano, 2013. "Modeling and valuing make-up clauses in gas swing contracts," Energy Economics, Elsevier, vol. 35(C), pages 58-73.
    5. Christophe Barrera-Esteve & Florent Bergeret & Charles Dossal & Emmanuel Gobet & Asma Meziou & Rémi Munos & Damien Reboul-Salze, 2006. "Numerical Methods for the Pricing of Swing Options: A Stochastic Control Approach," Methodology and Computing in Applied Probability, Springer, vol. 8(4), pages 517-540, December.
    6. 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.
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    Cited by:

    1. 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.
    2. Carl Chiarella & Les Clewlow & Boda Kang, 2016. "The Evaluation Of Multiple Year Gas Sales Agreement With Regime Switching," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-25, February.
    3. Giorgia Callegaro & Luciano Campi & Valeria Giusto & Tiziano Vargiolu, 2017. "Utility indifference pricing and hedging for structured contracts in energy markets," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 85(2), pages 265-303, April.
    4. Christian Bender & Nikolai Dokuchaev, 2014. "A First-Order BSPDE for Swing Option Pricing: Classical Solutions," Papers 1402.6444, arXiv.org, revised Nov 2014.

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