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An option pricing model based on a renewable energy price index

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  • Xue, Jian
  • Ding, Jing
  • Zhao, Laijun
  • Zhu, Di
  • Li, Lei

Abstract

As a result of rapid socioeconomic development, the world is facing the simultaneous challenges of environmental pollution and resource depletion. How to promote the development of renewable, non-polluting energy is therefore essential. This could be achieved by supporting the rapid growth of a renewable energy financial market that includes various derivatives. To support such an effort, we designed an option contract model based on a renewable energy price index using data from the current development status of energy financial markets. To construct a renewable energy price index, we chose the daily electricity price value from the Nord Pool exchange system from January 2017 to August 2019. Next, we used an auto-regressive integrated moving average (ARIMA) model to predict this price index and estimate the model's parameters. We then used the true value and the predicted value for Nord Pool to perform Monte Carlo simulation pricing for electricity price index options in September 2019, and calculated the relative error. We found that the option contract's design for the renewable energy price index was designed reasonably. The ARIMA model predicted the renewable electricity price index accurately, and the Monte Carlo simulation pricing was reasonable and practical. The option contract for renewable energy price index can effectively explore the energy financial markets varieties and promote the global development of renewable energy sources.

Suggested Citation

  • Xue, Jian & Ding, Jing & Zhao, Laijun & Zhu, Di & Li, Lei, 2022. "An option pricing model based on a renewable energy price index," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221023653
    DOI: 10.1016/j.energy.2021.122117
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    1. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    2. Schwert, C.W., 1989. "Margin Requirements And Stock Volatility," Papers t6, Columbia - Center for Futures Markets.
    3. Ma Yonghong & Wu Zhiyong & Ai Mingye & Wang Wei, 2016. "The Construction and Application of a New Exchange Rate Forecast Model Combining ARIMA with a Chaotic BP Algorithm," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(6), pages 1481-1495, June.
    4. L.A. Abbas-Turki & S. Vialle & Bernard Lapeyre & P. Mercier, 2014. "Pricing derivatives on graphics processing units using Monte Carlo simulation," Post-Print hal-01667067, HAL.
    5. C. J. Corrado & Tie Su, 1997. "Implied volatility skews and stock return skewness and kurtosis implied by stock option prices," The European Journal of Finance, Taylor & Francis Journals, vol. 3(1), pages 73-85, March.
    6. Niu, Hongli & Wang, Jun, 2017. "Return volatility duration analysis of NYMEX energy futures and spot," Energy, Elsevier, vol. 140(P1), pages 837-849.
    7. Jyothi Unnikrishnan & Kodakanallur Krishnaswamy Suresh, 2016. "Modelling the Impact of Government Policies on Import on Domestic Price of Indian Gold Using ARIMA Intervention Method," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2016, pages 1-6, September.
    8. Allen, David E. & Gao, Jiti & McAleer, Michael, 2009. "Modelling and managing financial risk: An overview," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2521-2524.
    9. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    10. Šaltytė Benth, Jūratė & Benth, Fred Espen, 2012. "A critical view on temperature modelling for application in weather derivatives markets," Energy Economics, Elsevier, vol. 34(2), pages 592-602.
    11. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    12. Boyle, Phelim P., 1977. "Options: A Monte Carlo approach," Journal of Financial Economics, Elsevier, vol. 4(3), pages 323-338, May.
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    7. Barbosa, Maria de Fatima & Street, Alexandre & Fanzeres, Bruno, 2024. "A Tailored Derivative Instrument to Mitigate the Price-and-Quantity Risk Faced by Wind Power Companies," Energy Economics, Elsevier, vol. 136(C).

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