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Modelling spikes and pricing swing options in electricity markets

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  • Ben Hambly
  • Sam Howison
  • Tino Kluge
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    Abstract

    Most electricity markets exhibit high volatilities and occasional distinctive price spikes, which result in demand for derivative products which protect the holder against high prices. In this paper we examine a simple spot price model that is the exponential of the sum of an Ornstein-Uhlenbeck and an independent mean-reverting pure jump process. We derive the moment generating function as well as various approximations to the probability density function of the logarithm of the spot price process at maturity T. Hence we are able to calibrate the model to the observed forward curve and present semi-analytic formulae for premia of path-independent options as well as approximations to call and put options on forward contracts with and without a delivery period. In order to price path-dependent options with multiple exercise rights like swing contracts a grid method is utilized which in turn uses approximations to the conditional density of the spot process.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/14697680802596856
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Quantitative Finance.

    Volume (Year): 9 (2009)
    Issue (Month): 8 ()
    Pages: 937-949

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    Handle: RePEc:taf:quantf:v:9:y:2009:i:8:p:937-949

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    Web page: http://www.tandfonline.com/RQUF20

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    Related research

    Keywords: Energy derivatives; Financial mathematics; Stochastic jumps; Numerical methods for option pricing; Continuous time models; Derivative pricing models;

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    Cited by:
    1. Álvaro Cartea & Carlos González-Pedraz, 2010. "How much should we pay for interconnecting electricity markets? A real options approach," Business Economics Working Papers wb103206, Universidad Carlos III, Departamento de Economía de la Empresa.
    2. Caldana, Ruggero & Fusai, Gianluca, 2013. "A general closed-form spread option pricing formula," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4893-4906.
    3. Marcus Eriksson & Jukka Lempa & Trygve Kastberg Nilssen, 2013. "Swing options in commodity markets: A multidimensional L\'evy diffusion model," Papers 1302.6399, arXiv.org.
    4. Janczura, Joanna & Trueck, Stefan & Weron, Rafal & Wolff, Rodney, 2012. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," MPRA Paper 39277, University Library of Munich, Germany.
    5. Marcus Eriksson & Jukka Lempa & Trygve Nilssen, 2014. "Swing options in commodity markets: a multidimensional Lévy diffusion model," Computational Statistics, Springer, vol. 79(1), pages 31-67, February.
    6. Patrick Henaff & Ismail Laachir & Francesco Russo, 2013. "Gas storage valuation and hedging. A quantification of the model risk," Papers 1312.3789, arXiv.org.
    7. Coulon, Michael & Powell, Warren B. & Sircar, Ronnie, 2013. "A model for hedging load and price risk in the Texas electricity market," Energy Economics, Elsevier, vol. 40(C), pages 976-988.

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