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An equilibrium pricing model for weather derivatives in a multi-commodity setting

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  • Lee, Yongheon
  • Oren, Shmuel S.

Abstract

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company's profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard methodologies used for derivative pricing in complete markets. In this paper, we develop an equilibrium pricing model for weather derivatives in a multi-commodity setting. The model is constructed in the context of a stylized economy where agents optimize their hedging portfolios which include weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand resulting from hedging activities and the supply by the underwriter are combined in an equilibrium pricing model under the assumption that all agents maximize some risk averse utility function. We analyze the gains due to the inclusion of weather derivatives in hedging portfolios and examine the components of that gain attributable to hedging and to risk sharing.

Suggested Citation

  • Lee, Yongheon & Oren, Shmuel S., 2009. "An equilibrium pricing model for weather derivatives in a multi-commodity setting," Energy Economics, Elsevier, vol. 31(5), pages 702-713, September.
    • Handle: RePEc:eee:eneeco:v:31:y:2009:i:5:p:702-713
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    References listed on IDEAS

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    3. Wolfgang Karl Hardle and Maria Osipenko, 2012. "Spatial Risk Premium on Weather Derivatives and Hedging Weather Exposure in Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    4. Traian A. Pirvu & Huayue Zhang, 2012. "A Multi Period Equilibrium Pricing Model," Papers 1205.6193, arXiv.org.
    5. Kanamura, Takashi & Homann, Lasse & Prokopczuk, Marcel, 2021. "Pricing analysis of wind power derivatives for renewable energy risk management," Applied Energy, Elsevier, vol. 304(C).
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    7. Bertrand, Jean-Louis & Brusset, Xavier & Fortin, Maxime, 2015. "Assessing and hedging the cost of unseasonal weather: Case of the apparel sector," European Journal of Operational Research, Elsevier, vol. 244(1), pages 261-276.
    8. Takuji Matsumoto & Yuji Yamada, 2021. "Customized yet Standardized Temperature Derivatives: A Non-Parametric Approach with Suitable Basis Selection for Ensuring Robustness," Energies, MDPI, vol. 14(11), pages 1-24, June.
    9. Yuji Yamada & Takuji Matsumoto, 2021. "Going for Derivatives or Forwards? Minimizing Cashflow Fluctuations of Electricity Transactions on Power Markets," Energies, MDPI, vol. 14(21), pages 1-28, November.
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    12. Javier Orlando Pantoja Robayo & Andrea Roncoroni, 2012. "Optimal Static Hedging of Energy Price and Volume Risk: Closed-Form Results," Documentos de Trabajo de Valor Público 10668, Universidad EAFIT.
    13. Takino, Kazuhiro, 2016. "An equilibrium model for the OTC derivatives market with a collateral agreement," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 41-55.
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