IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/29958.html
   My bibliography  Save this paper

Power Spot Price Models with negative Prices

Author

Listed:
  • Schneider, Stefan
  • Schneider, Stefan

Abstract

Negative prices for electricity are a novelty in European power markets. At the German EEX spot market negative hourly prices have since occurred frequently, down to values as extreme as minus several hundred €/MWh. However, in some non-European markets as USA, Australia and Canada, negative prices are a characteristic for a longer period already. Negative prices are in fact natural for electricity spot trading: plant flexibility is limited and costly, thus, incurring a negative price for an hour can nevertheless be economically optimal overall. Negative prices pose a basic problem to stochastic price modelling: going from prices to log-prices is not possible. So far, this has been dealt with by “workarounds”. However, here a thorough approach is advocated, based on the area hyperbolic sine transformation. The transformation is applied to spot modelling of the German EEX, the ERCOT West Texas market and the exemplary valuation of an option. It is concluded that the area hyperbolic sine transform is well and naturally suited as a starting point for modelling negative power prices. It can be integrated in common stochastic price models without adding much complexity. Moreover, this transformation might be in general more appropriate for power prices than the log transformation, considering fundamentals of power price formation. Eventually, a thorough treatment of negative prices is indispensable since they significantly affect business.

Suggested Citation

  • Schneider, Stefan & Schneider, Stefan, 2010. "Power Spot Price Models with negative Prices," MPRA Paper 29958, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:29958
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/29958/1/MPRA_paper_29958.pdf
    File Function: original version
    Download Restriction: no

    References listed on IDEAS

    as
    1. Damiano Brigo & Fabio Mercurio & Giulio Sartorelli, 2003. "Alternative asset-price dynamics and volatility smile," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 173-183.
    2. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    3. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    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. Lars Ivar Hagfors & Hilde Hørthe Kamperud & Florentina Paraschiv & Marcel Prokopczuk & Alma Sator & Sjur Westgaard, 2016. "Prediction of extreme price occurrences in the German day-ahead electricity market," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1929-1948, December.
    2. Keles, Dogan & Genoese, Massimo & Möst, Dominik & Fichtner, Wolf, 2012. "Comparison of extended mean-reversion and time series models for electricity spot price simulation considering negative prices," Energy Economics, Elsevier, vol. 34(4), pages 1012-1032.
    3. Almut E. D. Veraart & Luitgard A. M. Veraart, 2012. "Modelling electricity day–ahead prices by multivariate Lévy semistationary processes," CREATES Research Papers 2012-13, Department of Economics and Business Economics, Aarhus University.
    4. Arvesen, Ø. & Medbø, V. & Fleten, S.-E. & Tomasgard, A. & Westgaard, S., 2013. "Linepack storage valuation under price uncertainty," Energy, Elsevier, vol. 52(C), pages 155-164.
    5. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien De Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.

    More about this item

    Keywords

    energy spot price modeling; electricity spot markets; negative prices; EEX;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    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:pra:mprapa:29958. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter) or (Rebekah McClure). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.