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A Numerical Method for Pricing Electricity Derivatives for Jump-Diffusion Processes Based on Continuous Time Lattices

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  • Albanese, Claudio
  • Lo, Harry
  • Stathis, Tompaidis

Abstract

We present a numerical method for pricing derivatives on electricity prices. The method is based on approximating the generator of the underlying process and can be applied for stochastic processes that are combinations of diusions and jump processes. The method is accurate even in the case of processes with fast mean-reversion and jumps of large magnitude. We illustrate the speed and accuracy of the method by pricing European and Bermudan options and calculating the hedge ratios of European options for the Geman-Roncoroni model for electricity prices.

Suggested Citation

  • Albanese, Claudio & Lo, Harry & Stathis, Tompaidis, 2006. "A Numerical Method for Pricing Electricity Derivatives for Jump-Diffusion Processes Based on Continuous Time Lattices," MPRA Paper 5245, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:5245
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    File URL: https://mpra.ub.uni-muenchen.de/5245/1/MPRA_paper_5245.pdf
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    References listed on IDEAS

    as
    1. Helyette Geman & A. Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," Post-Print halshs-00144198, HAL.
    2. repec:dau:papers:123456789/1433 is not listed on IDEAS
    3. Hélyette Geman & Andrea Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1225-1262, May.
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    Citations

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    Cited by:

    1. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    2. Mitra, Sovan & Date, Paresh & Mamon, Rogemar & Wang, I-Chieh, 2013. "Pricing and risk management of interest rate swaps," European Journal of Operational Research, Elsevier, vol. 228(1), pages 102-111.
    3. Ethem Çanakoğlu & Esra Adıyeke, 2020. "Comparison of Electricity Spot Price Modelling and Risk Management Applications," Energies, MDPI, vol. 13(18), pages 1-22, September.
    4. Niall Farrell, Mel T. Devine, William T. Lee, James P. Gleeson, and Sean Lyons, 2017. "Specifying An Efficient Renewable Energy Feed-in Tariff," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    5. Islyaev, Suren & Date, Paresh, 2015. "Electricity futures price models: Calibration and forecasting," European Journal of Operational Research, Elsevier, vol. 247(1), pages 144-154.
    6. Helyette Geman & Stelios Kourouvakalis, 2008. "A Lattice-Based Method for Pricing Electricity Derivatives Under the Threshold Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(5-6), pages 531-567.
    7. Kourouvakalis, Stylianos, 2008. "Méthodes numériques pour la valorisation d'options swings et autres problèmes sur les matières premières," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/116 edited by Geman, Hélyette.

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    More about this item

    Keywords

    Electricity derivatives; operator methods;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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