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Gas Storage Valuation and Hedging: A Quantification of Model Risk

Author

Listed:
  • Patrick Hénaff

    (IAE Paris, Université Paris I-Panthéon Sorbonne, 75006 Paris, France)

  • Ismail Laachir

    (Ismail Laachir, Zeliade Systems, 56 Rue Jean-Jacques Rousseau, 75001 Paris, France)

  • Francesco Russo

    (Francesco Russo, ENSTA ParisTech, Unité de Mathématiques Appliquées, 91120 Palaiseau, France)

Abstract

This paper focuses on the valuation and hedging of gas storage facilities, using a spot-based valuation framework coupled with a financial hedging strategy implemented with futures contracts. The contributions of this paper are two-fold. Firstly, we propose a model that unifies the dynamics of the futures curve and spot price, and accounts for the main stylized facts of the US natural gas market such as seasonality and the presence of price spikes in the spot market. Secondly, we evaluate the associated model risk, and show not only that the valuation is strongly dependent upon the dynamics of the spot price, but more importantly that the hedging strategy commonly used in the industry leaves the storage operator with significant residual price risk.

Suggested Citation

  • Patrick Hénaff & Ismail Laachir & Francesco Russo, 2018. "Gas Storage Valuation and Hedging: A Quantification of Model Risk," IJFS, MDPI, vol. 6(1), pages 1-27, March.
    • Handle: RePEc:gam:jijfss:v:6:y:2018:i:1:p:27-:d:134807
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    References listed on IDEAS

    as
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    Cited by:

    1. Nicolas Curin & Michael Kettler & Xi Kleisinger-Yu & Vlatka Komaric & Thomas Krabichler & Josef Teichmann & Hanna Wutte, 2021. "A deep learning model for gas storage optimization," Papers 2102.01980, arXiv.org, revised Mar 2021.
    2. Asl, Mahdi Ghaemi & Canarella, Giorgio & Miller, Stephen M., 2021. "Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies," Resources Policy, Elsevier, vol. 71(C).
    3. Leunglung Chan, 2018. "Editorial for Special Issue “Finance, Financial Risk Management and their Applications”," IJFS, MDPI, vol. 6(4), pages 1-3, October.
    4. Nicolas Curin & Michael Kettler & Xi Kleisinger-Yu & Vlatka Komaric & Thomas Krabichler & Josef Teichmann & Hanna Wutte, 2021. "A deep learning model for gas storage optimization," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1021-1037, December.

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