IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v288y2021i1p318-330.html
   My bibliography  Save this article

Gas storage valuation in incomplete markets

Author

Listed:
  • Löhndorf, Nils
  • Wozabal, David

Abstract

Natural gas storage valuation is an important problem in energy trading, yet most valuation approaches are based on heuristics or ignore that gas markets are incomplete. We propose an exact valuation model for incomplete gas markets based on multistage stochastic programming. Market incompleteness structurally changes the problem of storage valuation and asset backed trading and the resulting model requires analysis of a combined control problem of storage operation and futures trading that takes risk preferences into account. As the problem is subject to the curse of dimensionality, we reduce the stochastic process to a scenario lattice and solve the resulting problem using stochastic dual dynamic programming. We show that the intrinsic value of storage corresponds to the value under perfect risk aversion and that the rolling intrinsic value, which is popular among practitioners and has been found to be near-optimal when markets are complete, is an inconsistent price rule in incomplete markets. Our results inform managerial decisions on risk management and asset pricing for natural gas highlighting the importance of explicitly modeling risk preferences.

Suggested Citation

  • Löhndorf, Nils & Wozabal, David, 2021. "Gas storage valuation in incomplete markets," European Journal of Operational Research, Elsevier, vol. 288(1), pages 318-330.
    • Handle: RePEc:eee:ejores:v:288:y:2021:i:1:p:318-330
    DOI: 10.1016/j.ejor.2020.05.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720304902
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2020.05.044?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shapiro, Alexander & Tekaya, Wajdi & da Costa, Joari Paulo & Soares, Murilo Pereira, 2013. "Risk neutral and risk averse Stochastic Dual Dynamic Programming method," European Journal of Operational Research, Elsevier, vol. 224(2), pages 375-391.
    2. Nils Löhndorf & David Wozabal & Stefan Minner, 2013. "Optimizing Trading Decisions for Hydro Storage Systems Using Approximate Dual Dynamic Programming," Operations Research, INFORMS, vol. 61(4), pages 810-823, August.
    3. Nicola Secomandi, 2015. "Merchant Commodity Storage Practice Revisited," Operations Research, INFORMS, vol. 63(5), pages 1131-1143, October.
    4. Petter Bjerksund & Gunnar Stensland & Frank Vagstad, 2011. "Gas Storage Valuation: Price Modelling v. Optimization Methods," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 203-228.
    5. Shapiro, Alexander, 2011. "Analysis of stochastic dual dynamic programming method," European Journal of Operational Research, Elsevier, vol. 209(1), pages 63-72, February.
    6. Rene Carmona & Michael Ludkovski, 2010. "Valuation of energy storage: an optimal switching approach," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 359-374.
    7. Andy Philpott & Vitor de Matos & Erlon Finardi, 2013. "On Solving Multistage Stochastic Programs with Coherent Risk Measures," Operations Research, INFORMS, vol. 61(4), pages 957-970, August.
    8. Matt Thompson & Matt Davison & Henning Rasmussen, 2009. "Natural gas storage valuation and optimization: A real options application," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(3), pages 226-238, April.
    9. Andrzej Ruszczyński & Alexander Shapiro, 2006. "Conditional Risk Mappings," Mathematics of Operations Research, INFORMS, vol. 31(3), pages 544-561, August.
    10. Löhndorf, Nils & Shapiro, Alexander, 2019. "Modeling time-dependent randomness in stochastic dual dynamic programming," European Journal of Operational Research, Elsevier, vol. 273(2), pages 650-661.
    11. Felix, Bastian Joachim & Weber, Christoph, 2012. "Gas storage valuation applying numerically constructed recombining trees," European Journal of Operational Research, Elsevier, vol. 216(1), pages 178-187.
    12. Nicola Secomandi, 2010. "Optimal Commodity Trading with a Capacitated Storage Asset," Management Science, INFORMS, vol. 56(3), pages 449-467, March.
    13. Susanne Klöppel & Martin Schweizer, 2007. "Dynamic Indifference Valuation Via Convex Risk Measures," Mathematical Finance, Wiley Blackwell, vol. 17(4), pages 599-627, October.
    14. J. Bonnans & Zhihao Cen & Thibault Christel, 2012. "Energy contracts management by stochastic programming techniques," Annals of Operations Research, Springer, vol. 200(1), pages 199-222, November.
    15. Guoming Lai & François Margot & Nicola Secomandi, 2010. "An Approximate Dynamic Programming Approach to Benchmark Practice-Based Heuristics for Natural Gas Storage Valuation," Operations Research, INFORMS, vol. 58(3), pages 564-582, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joakim Dimoski & Stein-Erik Fleten & Nils Löhndorf & Sveinung Nersten, 2023. "Dynamic hedging for the real option management of hydropower production with exchange rate risks," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 525-554, June.
    2. Palma, Alessia & Paltrinieri, Andrea & Goodell, John W. & Oriani, Marco Ercole, 2024. "The black box of natural gas market: Past, present, and future," International Review of Financial Analysis, Elsevier, vol. 94(C).
    3. Nadarajah, Selvaprabu & Secomandi, Nicola, 2023. "A review of the operations literature on real options in energy," European Journal of Operational Research, Elsevier, vol. 309(2), pages 469-487.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nadarajah, Selvaprabu & Secomandi, Nicola, 2023. "A review of the operations literature on real options in energy," European Journal of Operational Research, Elsevier, vol. 309(2), pages 469-487.
    2. Secomandi, Nicola & Seppi, Duane J., 2014. "Real Options and Merchant Operations of Energy and Other Commodities," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 6(3-4), pages 161-331, July.
    3. Daniel R. Jiang & Warren B. Powell, 2015. "Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 525-543, August.
    4. Mahmutoğulları, Ali İrfan & Çavuş, Özlem & Aktürk, M. Selim, 2018. "Bounds on risk-averse mixed-integer multi-stage stochastic programming problems with mean-CVaR," European Journal of Operational Research, Elsevier, vol. 266(2), pages 595-608.
    5. Anna Maria Gambaro & Nicola Secomandi, 2021. "A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 47-67, January.
    6. Joakim Dimoski & Stein-Erik Fleten & Nils Löhndorf & Sveinung Nersten, 2023. "Dynamic hedging for the real option management of hydropower production with exchange rate risks," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 525-554, June.
    7. Nicola Secomandi, 2015. "Merchant Commodity Storage Practice Revisited," Operations Research, INFORMS, vol. 63(5), pages 1131-1143, October.
    8. Selvaprabu Nadarajah & François Margot & Nicola Secomandi, 2015. "Relaxations of Approximate Linear Programs for the Real Option Management of Commodity Storage," Management Science, INFORMS, vol. 61(12), pages 3054-3076, December.
    9. Bastian Felix, 2012. "Gas Storage Valuation: A Comparative Simulation Study," EWL Working Papers 1201, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Apr 2014.
    10. Felix, Bastian Joachim & Weber, Christoph, 2012. "Gas storage valuation applying numerically constructed recombining trees," European Journal of Operational Research, Elsevier, vol. 216(1), pages 178-187.
    11. Guoming Lai & Mulan X. Wang & Sunder Kekre & Alan Scheller-Wolf & Nicola Secomandi, 2011. "Valuation of Storage at a Liquefied Natural Gas Terminal," Operations Research, INFORMS, vol. 59(3), pages 602-616, June.
    12. Secomandi, Nicola, 2016. "A tutorial on portfolio-based control algorithms for merchant energy trading operations," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 1-13.
    13. Nadarajah, Selvaprabu & Margot, François & Secomandi, Nicola, 2017. "Comparison of least squares Monte Carlo methods with applications to energy real options," European Journal of Operational Research, Elsevier, vol. 256(1), pages 196-204.
    14. Cummins, Mark & Kiely, Greg & Murphy, Bernard, 2018. "Gas storage valuation under multifactor Lévy processes," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 167-184.
    15. D. Ávila & A. Papavasiliou & N. Löhndorf, 2022. "Parallel and distributed computing for stochastic dual dynamic programming," Computational Management Science, Springer, vol. 19(2), pages 199-226, June.
    16. Yangfang (Helen) Zhou & Alan Scheller‐Wolf & Nicola Secomandi & Stephen Smith, 2019. "Managing Wind‐Based Electricity Generation in the Presence of Storage and Transmission Capacity," Production and Operations Management, Production and Operations Management Society, vol. 28(4), pages 970-989, April.
    17. Schur, Rouven & Gönsch, Jochen & Hassler, Michael, 2019. "Time-consistent, risk-averse dynamic pricing," European Journal of Operational Research, Elsevier, vol. 277(2), pages 587-603.
    18. Guigues, Vincent & Shapiro, Alexander & Cheng, Yi, 2023. "Duality and sensitivity analysis of multistage linear stochastic programs," European Journal of Operational Research, Elsevier, vol. 308(2), pages 752-767.
    19. Lorenzo Reus & Rodolfo Prado, 2022. "Need to Meet Investment Goals? Track Synthetic Indexes with the SDDP Method," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 47-69, June.
    20. Nicola Secomandi & Guoming Lai & François Margot & Alan Scheller-Wolf & Duane J. Seppi, 2015. "Merchant Commodity Storage and Term-Structure Model Error," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 302-320, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:288:y:2021:i:1:p:318-330. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.