IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v13y2025i1p7-d1559951.html
   My bibliography  Save this article

Empirical Evidence of the Market Price of Risk for Delivery Periods

Author

Listed:
  • Annika Kemper

    (Center for Mathematical Economics (IMW), Bielefeld University, 33615 Bielefeld, Germany)

  • Maren Diane Schmeck

    (Center for Mathematical Economics (IMW), Bielefeld University, 33615 Bielefeld, Germany)

Abstract

In this paper, we provide empirical evidence of the market price of risk for delivery periods (MPDP) of electricity swap contracts. The MPDP enables an accurate pricing of such contracts in the presence of the delivery period such that the typical approximations can be avoided. In our empirical study, we focus on term-structure effects and identify the resulting MPDP. In presence of the Samuelson effect, we find the most pronounced MPDP close to maturity, while the MPDP disappears proportional to the Samuelson effect far away from maturity. Thus, our theory improves the pricing accuracy close to maturity.

Suggested Citation

  • Annika Kemper & Maren Diane Schmeck, 2025. "Empirical Evidence of the Market Price of Risk for Delivery Periods," Risks, MDPI, vol. 13(1), pages 1-20, January.
    • Handle: RePEc:gam:jrisks:v:13:y:2025:i:1:p:7-:d:1559951
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/13/1/7/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/13/1/7/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Viviana Fanelli & Maren Diane Schmeck, 2019. "On the seasonality in the implied volatility of electricity options," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1321-1337, August.
    2. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    3. Les Clewlow & Chris Strickland, 1999. "Valuing Energy Options in a One Factor Model Fitted to Forward Prices," Research Paper Series 10, Quantitative Finance Research Centre, University of Technology, Sydney.
    Full references (including those not matched with items on IDEAS)

    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. L. Schneider & B. Tavin, 2024. "Seasonal volatility in agricultural markets: modelling and empirical investigations," Annals of Operations Research, Springer, vol. 334(1), pages 7-58, March.
    2. Dong, Wenfeng & Kang, Boda, 2019. "Analysis of a multiple year gas sales agreement with make-up, carry-forward and indexation," Energy Economics, Elsevier, vol. 79(C), pages 76-96.
    3. Joanna Janczura & Aleksander Weron, 2008. "Modelling energy forward prices," HSC Research Reports HSC/08/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    4. E. Nasakkala & J. Keppo, 2008. "Hydropower with Financial Information," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(5-6), pages 503-529.
    5. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    6. de Jong, C.M. & Huisman, R., 2002. "Option Formulas for Mean-Reverting Power Prices with Spikes," ERIM Report Series Research in Management ERS-2002-96-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Goudenège, Ludovic & Molent, Andrea & Zanette, Antonino, 2022. "Moving average options: Machine learning and Gauss-Hermite quadrature for a double non-Markovian problem," European Journal of Operational Research, Elsevier, vol. 303(2), pages 958-974.
    8. Piccirilli, Marco & Schmeck, Maren Diane & Vargiolu, Tiziano, 2021. "Capturing the power options smile by an additive two-factor model for overlapping futures prices," Energy Economics, Elsevier, vol. 95(C).
    9. de Jong, C.M., 2005. "The Nature of Power Spikes: a regime-switch approach," ERIM Report Series Research in Management ERS-2005-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Hanfeld, Marc & Schlüter, Stephan, 2016. "Operating a swing option on today's gas markets: How least squares Monte Carlo works and why it is beneficial," FAU Discussion Papers in Economics 10/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    11. Joanna Janczura, 2012. "Pricing electricity derivatives within a Markov regime-switching model," Papers 1203.5442, arXiv.org.
    12. Matt Thompson, 2013. "Optimal Economic Dispatch and Risk Management of Thermal Power Plants in Deregulated Markets," Operations Research, INFORMS, vol. 61(4), pages 791-809, August.
    13. Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2021. "Moving average options: Machine Learning and Gauss-Hermite quadrature for a double non-Markovian problem," Papers 2108.11141, arXiv.org.
    14. Maren Diane Schmeck & Stefan Schwerin, 2021. "The Effect of Mean-Reverting Processes in the Pricing of Options in the Energy Market: An Arithmetic Approach," Risks, MDPI, vol. 9(5), pages 1-19, May.
    15. Lang, Joachim & Madlener, Reinhard, 2010. "Portfolio Optimization for Power Plants: The Impact of Credit Risk Mitigation and Margining," FCN Working Papers 11/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    16. Carme Frau & Viviana Fanelli, 2024. "Seasonality in commodity prices: new approaches for pricing plain vanilla options," Annals of Operations Research, Springer, vol. 336(1), pages 1089-1131, May.
    17. Rudiger Kiesel & Gero Schindlmayr & Reik Borger, 2009. "A two-factor model for the electricity forward market," Quantitative Finance, Taylor & Francis Journals, vol. 9(3), pages 279-287.
    18. Andreis, Luisa & Flora, Maria & Fontini, Fulvio & Vargiolu, Tiziano, 2020. "Pricing reliability options under different electricity price regimes," Energy Economics, Elsevier, vol. 87(C).
    19. Bisht Deepak & Laha, A. K., 2017. "Pricing Option on Commodity Futures under String Shock," IIMA Working Papers WP 2017-07-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    20. Carl Chiarella & Les Clewlow & Boda Kang, 2009. "Modelling and Estimating the Forward Price Curve in the Energy Market," Research Paper Series 260, Quantitative Finance Research Centre, University of Technology, Sydney.

    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:gam:jrisks:v:13:y:2025:i:1:p:7-:d:1559951. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.