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Pricing power derivatives: a two-factor jump-diffusion approach

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  • Villaplana Conde, Pablo

Abstract

We propose a two-factor jump-diffusion model with seasonality for the valuation of electricity future contracts. The model we propose is an extension of Schwartz and Smith (Management Science, 2000) and Lucia and Schwartz (Review of Derivatives Research, 2002), long-term / short-term model. One of the main contributions of the paper is the inclusion of a jump component, with a non-constant intensity process (probability of occurrence of jumps), in the short-term factor. We model the stochastic behaviour of the underlying (unobservable) state variables by Affine Diffusions (AD) and Affine Jump Diffusions (AJD). We obtain closed form formulas for the price of futures contracts using the results by Duffie, Pan and Singleton (Econometrica, 2000). We provide empirical evidence on the observed seasonality in risk premium, that has been documented in the PJM market. This paper also complements the results provided by the equilibrium model of Bessembinder and Lemmon (Journal of Finance, 2002), and provides an easy methodology to extract risk-neutral parameters from forward data.

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  • Villaplana Conde, Pablo, 2003. "Pricing power derivatives: a two-factor jump-diffusion approach," DEE - Working Papers. Business Economics. WB wb031805, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
  • Handle: RePEc:cte:wbrepe:wb031805
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    References listed on IDEAS

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    Cited by:

    1. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market," Energy Economics, Elsevier, vol. 32(2), pages 302-312, March.
    2. John Crosby, 2008. "A multi-factor jump-diffusion model for commodities," Quantitative Finance, Taylor & Francis Journals, vol. 8(2), pages 181-200.
    3. N. K. Nomikos & O. Soldatos, 2008. "Using Affine Jump Diffusion Models for Modelling and Pricing Electricity Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(1), pages 41-71.
    4. Noufel Frikha & Vincent Lemaire, 2012. "Joint Modelling of Gas and Electricity spot prices," Post-Print hal-00421289, HAL.
    5. Weron, Rafal, 2008. "Market price of risk implied by Asian-style electricity options and futures," Energy Economics, Elsevier, vol. 30(3), pages 1098-1115, May.
    6. Kanamura, Takashi & O[combining macron]hashi, Kazuhiko, 2008. "On transition probabilities of regime switching in electricity prices," Energy Economics, Elsevier, vol. 30(3), pages 1158-1172, May.
    7. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool," Energy Policy, Elsevier, vol. 38(10), pages 5671-5683, October.
    8. Mari, Carlo, 2006. "Regime-switching characterization of electricity prices dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 552-564.
    9. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
    10. Abadie, Luis María & Chamorro, José Manuel, 2021. "Evaluation of a cross-border electricity interconnection: The case of Spain-France," Energy, Elsevier, vol. 233(C).
    11. 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.
    12. 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.
    13. 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.
    14. Guo, Zi-Yi, 2017. "Models with Short-Term Variations and Long-Term Dynamics in Risk Management of Commodity Derivatives," EconStor Preprints 167619, ZBW - Leibniz Information Centre for Economics.
    15. Thilo Meyer-Brandis & Peter Tankov, 2008. "Multi-Factor Jump-Diffusion Models Of Electricity Prices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(05), pages 503-528.
    16. Shao, Chengwu & Bhar, Ramaprasad & Colwell, David B., 2015. "A multi-factor model with time-varying and seasonal risk premiums for the natural gas market," Energy Economics, Elsevier, vol. 50(C), pages 207-214.
    17. Jacobs, Kris & Li, Yu & Pirrong, Craig, 2022. "Supply, demand, and risk premiums in electricity markets," Journal of Banking & Finance, Elsevier, vol. 135(C).
    18. Islyaev, Suren & Date, Paresh, 2015. "Electricity futures price models: Calibration and forecasting," European Journal of Operational Research, Elsevier, vol. 247(1), pages 144-154.
    19. Abadie, Luis M. & Goicoechea, Nestor, 2022. "Optimal management of a mega pumped hydro storage system under stochastic hourly electricity prices in the Iberian Peninsula," Energy, Elsevier, vol. 252(C).
    20. Luis M. Abadie, 2021. "Energy Market Prices in Times of COVID-19: The Case of Electricity and Natural Gas in Spain," Energies, MDPI, vol. 14(6), pages 1-17, March.
    21. Christian Laudag'e & Florian Aichinger & Sascha Desmettre, 2023. "A Comparative Study of Factor Models for Different Periods of the Electricity Spot Price Market," Papers 2306.07731, arXiv.org, revised Apr 2024.
    22. Jan Seifert & Marliese Uhrig-Homburg, 2007. "Modelling jumps in electricity prices: theory and empirical evidence," Review of Derivatives Research, Springer, vol. 10(1), pages 59-85, January.

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