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Wind Put Barrier Options Pricing Based on the Nordix Index

Author

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  • Yeny E. Rodríguez

    (Departamento de Estudios Contable y Financiero, Escuela de Economía y Finanzas, Universidad Icesi, 760008 Cali, Colombia)

  • Miguel A. Pérez-Uribe

    (Departamento de Estudios Contable y Financiero, Escuela de Economía y Finanzas, Universidad Icesi, 760008 Cali, Colombia)

  • Javier Contreras

    (E.T.S. de Ingeniería Industrial, University of Castilla—La Mancha, 13071 Ciudad Real, Spain)

Abstract

Wind power generators face risks derived from fluctuations in market prices and variability in power production, generated by their high dependence on wind speed. These risks could be hedged using weather financial instruments. In this research, we design and price an up-and-in European wind put barrier option using Monte Carlo simulation. Under the existence of a structured weather market, wind producers may purchase an up-and-in European wind barrier put option to hedge wind fluctuations, allowing them to recover their investments and maximise their profits. We use a wind speed index as the underlying index of the barrier option, which captures risk from wind power generation and the Autoregressive Fractionally Integrated Moving Average (ARFIMA) to model the wind speed. This methodology is applied in the Colombian context, an electricity market affected by the El Niño phenomenon. We find that when the El Niño phenomenon occurs, there are incentives for wind generators to sell their energy to the system because their costs, including the put option price, are lower than the power prices. This research aims at encouraging policymakers and governments to promote renewable energy sources and a financial market to trade options to reduce uncertainty in the electrical system due to climate phenomena.

Suggested Citation

  • Yeny E. Rodríguez & Miguel A. Pérez-Uribe & Javier Contreras, 2021. "Wind Put Barrier Options Pricing Based on the Nordix Index," Energies, MDPI, vol. 14(4), pages 1-14, February.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:1177-:d:504014
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    References listed on IDEAS

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    Cited by:

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    4. Faridul Islam & Aviral Kumar Tiwari & Wing-Keung Wong, 2021. "Editorial and Ideas for Research Using Mathematical and Statistical Models for Energy with Applications," Energies, MDPI, vol. 14(22), pages 1-4, November.
    5. Liu, Yue & Tian, Lixin & Sun, Huaping & Zhang, Xiling & Kong, Chuimin, 2022. "Option pricing of carbon asset and its application in digital decision-making of carbon asset," Applied Energy, Elsevier, vol. 310(C).
    6. Yuji Yamada & Takuji Matsumoto, 2023. "Construction of Mixed Derivatives Strategy for Wind Power Producers," Energies, MDPI, vol. 16(9), pages 1-26, April.
    7. Michele Bufalo & Antonio Di Bari & Giovanni Villani, 2023. "A Compound Up-and-In Call like Option for Wind Projects Pricing," Risks, MDPI, vol. 11(5), pages 1-13, May.
    8. Shinji Kuno & Kenji Tanaka & Yuji Yamada, 2022. "Effectiveness and Feasibility of Market Makers for P2P Electricity Trading," Energies, MDPI, vol. 15(12), pages 1-24, June.
    9. Takuji Matsumoto & Yuji Yamada, 2023. "Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power," Energies, MDPI, vol. 16(7), pages 1-22, March.

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