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Energy Spot Price Models And Spread Options Pricing

Author

Listed:
  • SAMUEL HIKSPOORS

    (Department of Statistics, University of Toronto, 100 St. George Street, Toronto, Canada M5S 3G3, Canada)

  • SEBASTIAN JAIMUNGAL

    (Department of Statistics, University of Toronto, 100 St. George Street, Toronto, Canada M5S 3G3, Canada;
    Mathematical Finance Program, University of Toronto, 219 – 720 Spadina Ave, Toronto, Canada M5S 2T9, Canada)

Abstract

In this article, we construct forward price curves and value a class of two asset exchange options for energy commodities. We model the spot prices using an affine two-factor mean-reverting process with and without jumps. Within this modeling framework, we obtain closed form results for the forward prices in terms of elementary functions. Through measure changes induced by the forward price process, we further obtain closed form pricing equations for spread options on the forward prices. For completeness, we address both an Actuarial and a risk-neutral approach to the valuation problem. Finally, we provide a calibration procedure and calibrate our model to the NYMEX Light Sweet Crude Oil spot and futures data, allowing us to extract the implied market prices of risk for this commodity.

Suggested Citation

  • Samuel Hikspoors & Sebastian Jaimungal, 2007. "Energy Spot Price Models And Spread Options Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(07), pages 1111-1135.
    • Handle: RePEc:wsi:ijtafx:v:10:y:2007:i:07:n:s0219024907004573
    DOI: 10.1142/S0219024907004573
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    Citations

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    Cited by:

    1. Edward P. C. Kao & Weiwei Xie, 2017. "Pricing spread options by generalized bivariate edgeworth expansion," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(02n03), pages 1-30, June.
    2. 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).
    3. Jun Maekawa & Koji Shimada, 2019. "A Speculative Trading Model for the Electricity Market: Based on Japan Electric Power Exchange," Energies, MDPI, vol. 12(15), pages 1-15, July.
    4. 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.
    5. Mario Figueiredo & Yuri F. Saporito, 2023. "Forecasting the term structure of commodities future prices using machine learning," Digital Finance, Springer, vol. 5(1), pages 57-90, March.
    6. Andreis, Luisa & Flora, Maria & Fontini, Fulvio & Vargiolu, Tiziano, 2020. "Pricing reliability options under different electricity price regimes," Energy Economics, Elsevier, vol. 87(C).
    7. Roncoroni, Andrea & Id Brik, Rachid, 2017. "Hedging size risk: Theory and application to the US gas market," Energy Economics, Elsevier, vol. 64(C), pages 415-437.
    8. 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.
    9. 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.
    10. Max F. Schöne & Stefan Spinler, 2017. "A four-factor stochastic volatility model of commodity prices," Review of Derivatives Research, Springer, vol. 20(2), pages 135-165, July.
    11. Cartea, Álvaro & Jaimungal, Sebastian & Qin, Zhen, 2019. "Speculative trading of electricity contracts in interconnected locations," Energy Economics, Elsevier, vol. 79(C), pages 3-20.
    12. Kobari, L. & Jaimungal, S. & Lawryshyn, Y., 2014. "A real options model to evaluate the effect of environmental policies on the oil sands rate of expansion," Energy Economics, Elsevier, vol. 45(C), pages 155-165.

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