IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2011.03987.html
   My bibliography  Save this paper

Unifying the theory of storage and the risk premium by an unobservable intrinsic electricity price

Author

Listed:
  • Wieger Hinderks
  • Ralf Korn
  • Andreas Wagner

Abstract

In this paper we introduce a new concept for modelling electricity prices through the introduction of an unobservable intrinsic electricity price $p(\tau)$. We use it to connect the classical theory of storage with the concept of a risk premium. We derive prices for all common contracts such as the intraday spot price, the day-ahead spot price, and futures prices. Finally, we propose an explicit model from the class of structural models and conduct an empirical analysis, where we find an overall negative risk premium.

Suggested Citation

  • Wieger Hinderks & Ralf Korn & Andreas Wagner, 2020. "Unifying the theory of storage and the risk premium by an unobservable intrinsic electricity price," Papers 2011.03987, arXiv.org.
  • Handle: RePEc:arx:papers:2011.03987
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2011.03987
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    2. Rick Steinert & Florian Ziel, 2018. "Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures," Papers 1801.10583, arXiv.org.
    3. Viehmann, Johannes, 2011. "Risk premiums in the German day-ahead Electricity Market," Energy Policy, Elsevier, vol. 39(1), pages 386-394, January.
    4. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    5. Benth, Fred Espen & Cartea, Álvaro & Kiesel, Rüdiger, 2008. "Pricing forward contracts in power markets by the certainty equivalence principle: Explaining the sign of the market risk premium," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2006-2021, October.
    6. René Aïd & Luciano Campi & Adrien Nguyen Huu & Nizar Touzi, 2009. "A Structural Risk-Neutral Model Of Electricity Prices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(07), pages 925-947.
    7. 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.
    8. Juri Hinz & Lutz Von Grafenstein & Michel Verschuere & Martina Wilhelm, 2005. "Pricing electricity risk by interest rate methods," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 49-60.
    9. David Heath & Robert Jarrow & Andrew Morton, 2008. "Bond Pricing And The Term Structure Of Interest Rates: A New Methodology For Contingent Claims Valuation," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 13, pages 277-305, World Scientific Publishing Co. Pte. Ltd..
    10. Latini, Luca & Piccirilli, Marco & Vargiolu, Tiziano, 2019. "Mean-reverting no-arbitrage additive models for forward curves in energy markets," Energy Economics, Elsevier, vol. 79(C), pages 157-170.
    11. Wieger Hinderks & Andreas Wagner & Ralf Korn, 2018. "A structural Heath-Jarrow-Morton framework for consistent intraday, spot, and futures electricity prices," Papers 1803.08831, arXiv.org, revised Jan 2019.
    12. M. T. Barlow, 2002. "A Diffusion Model For Electricity Prices," Mathematical Finance, Wiley Blackwell, vol. 12(4), pages 287-298, October.
    13. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    14. Lucia, Julio J. & Torró, Hipòlit, 2011. "On the risk premium in Nordic electricity futures prices," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 750-763, October.
    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. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    2. Wieger Hinderks & Andreas Wagner & Ralf Korn, 2018. "A structural Heath-Jarrow-Morton framework for consistent intraday, spot, and futures electricity prices," Papers 1803.08831, arXiv.org, revised Jan 2019.
    3. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811, December.
    4. Iván Blanco, Juan Ignacio Peña, and Rosa Rodriguez, 2018. "Modelling Electricity Swaps with Stochastic Forward Premium Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    5. Benth, Fred Espen & Koekebakker, Steen, 2008. "Stochastic modeling of financial electricity contracts," Energy Economics, Elsevier, vol. 30(3), pages 1116-1157, May.
    6. Fred Espen Benth & Marco Piccirilli & Tiziano Vargiolu, 2017. "Additive energy forward curves in a Heath-Jarrow-Morton framework," Papers 1709.03310, arXiv.org, revised Jun 2018.
    7. repec:dui:wpaper:1504 is not listed on IDEAS
    8. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    9. George Daskalakis, Lazaros Symeonidis, Raphael N. Markellos, 2015. "Electricity futures prices in an emissions constrained economy: Evidence from European power markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    10. Olivier Feron & Pierre Gruet, 2020. "Estimation of the number of factors in a multi-factorial Heath-Jarrow-Morton model in electricity markets," Working Papers hal-02880824, HAL.
    11. 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.
    12. Kallabis, Thomas & Pape, Christian & Weber, Christoph, 2016. "The plunge in German electricity futures prices – Analysis using a parsimonious fundamental model," Energy Policy, Elsevier, vol. 95(C), pages 280-290.
    13. Anh Ngoc Lai & Constantin Mellios, 2016. "Valuation of commodity derivatives with an unobservable convenience yield," Post-Print halshs-01183166, HAL.
    14. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    15. 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.
    16. Paschke, Raphael & Prokopczuk, Marcel, 2010. "Commodity derivatives valuation with autoregressive and moving average components in the price dynamics," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2742-2752, November.
    17. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien de Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.
    18. Back, Janis & Prokopczuk, Marcel & Rudolf, Markus, 2013. "Seasonality and the valuation of commodity options," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 273-290.
    19. Zhang, Yue & Farnoosh, Arash, 2019. "Analyzing the dynamic impact of electricity futures on revenue and risk of renewable energy in China," Energy Policy, Elsevier, vol. 132(C), pages 678-690.
    20. Max F. Schöne & Stefan Spinler, 2017. "A four-factor stochastic volatility model of commodity prices," Review of Derivatives Research, Springer, vol. 20(2), pages 135-165, July.
    21. Fred Benth & Jukka Lempa, 2014. "Optimal portfolios in commodity futures markets," Finance and Stochastics, Springer, vol. 18(2), pages 407-430, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2011.03987. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.