IDEAS home Printed from https://ideas.repec.org/a/prs/recind/rei_0154-3229_2004_num_107_1_3053.html

Markets Design, Bidding Rules, and Long Memory in Electricity Prices

Author

Listed:
  • Sandro Sapio

Abstract

[eng] In uniform price, sealed-bid, day-ahead electricity auctions, the market price is set at the intersection between aggregate demand and supply functions constructed by a market operator. Each day, just one agent - the marginal generator - owns the market-clearing plant. Moreover, day-ahead auctions are embedded in multi-segment systems, wherein diverse protocols coexist and change over time. This complex environment leads to adoption of simple, adaptive bidding rules. Specifically, such a market design enables the emergence of two different types of routines, depending on whether the agent is a likely marginal or inframarginal generator. However, because of the uniform price mechanism, only the bidding behavior of the former can be reflected into market prices. Depending on the specific way marginal generators process past information to set their bids - « hyperbolic » or « exponential » - electricity prices are likely to display long- or short-memory. Using an analogy with the hyperbolic discounting - a quite robust behavioral bias in humans - a long-memory view of electricity prices is proposed. This insight is confirmed by spectral analysis of daily data from NordPool and CaIPX markets, in sharp contrast with most previous empirical studies. This paper underlines the importance of institutional settings in determining the relationship between individual behavior and market outcomes, and proposes an interesting mapping of bidding rules and models of information processing into the time series properties of market prices. [fre] Pour les enchères sous plis scellés et prix uniformes sur les marchés day ahead de l'électricité, le prix de marché est déterminé à l'intersection des fonctions d'offre et de demande agrégées construites par un opérateur de marché. Chaque jour, un seul agent (le générateur marginal) détient l'usine qui permet de solder le marché. De plus, les enchères day ahead sont intégrées dans des systèmes multi segments, dans lesquels divers protocoles coexistent et changent dans le temps. Cet environnement complexe conduit à l'adoption de règles d'enchères simples et adaptatives. Plus précisément, une telle configuration de marché autorise l'émergence de deux types différents de routines, selon que l'agent est un générateur marginal ou infra marginal. Cependant, du fait du mécanisme de prix uniforme, seul le comportement d'enchère du premier peut être reflété dans les prix de marchés. En fonction de la manière spécifique dont les générateurs marginaux traitent l'information passée pour déterminer leurs enchères (« hyperbolique » ou « exponentielle ») les prix de l'électricité sont susceptibles d'exhiber des effets de mémoire longue ou courte. En utilisant une analogie avec l'actualisation hyperbolique (un biais de comportement humain robuste) une conception en mémoire longue du prix de l'électricité est proposée. Cette intuition est confirmée par une analyse spectrale des données journalières issues des marchés NordPool et CalPX, en opposition forte avec de nombreuses études empiriques précédentes. Cet article souligne l'importance des accords institutionnels pour déterminer les relations entre les comportements individuels et les résultats du marché. Il propose une cartographie intéressante des règles d'enchères et des modèles de traitement de l'information selon les propriétés des séries temporelles des prix de marché.

Suggested Citation

  • Sandro Sapio, 2004. "Markets Design, Bidding Rules, and Long Memory in Electricity Prices," Revue d'Économie Industrielle, Programme National Persée, vol. 107(1), pages 151-170.
  • Handle: RePEc:prs:recind:rei_0154-3229_2004_num_107_1_3053
    DOI: 10.3406/rei.2004.3053
    Note: DOI:10.3406/rei.2004.3053
    as

    Download full text from publisher

    File URL: https://doi.org/10.3406/rei.2004.3053
    Download Restriction: no

    File URL: https://www.persee.fr/doc/rei_0154-3229_2004_num_107_1_3053
    Download Restriction: no

    File URL: https://libkey.io/10.3406/rei.2004.3053?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
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Fiorillo, Damiano & Sapio, Alessandro, 2019. "Energy saving in Italy in the late 1990s: Which role for non-monetary motivations?," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    2. Sandro Sapio, 2012. "Modeling the distribution of day-ahead electricity returns: a comparison," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1935-1949, December.
    3. Avci, Ezgi & Ketter, Wolfgang & van Heck, Eric, 2018. "Managing electricity price modeling risk via ensemble forecasting: The case of Turkey," Energy Policy, Elsevier, vol. 123(C), pages 390-403.
    4. Bottazzi, G. & Sapio, S. & Secchi, A., 2005. "Some statistical investigations on the nature and dynamics of electricity prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 54-61.
    5. Marossy, Zita, 2011. "A villamos energia áralakulásának egy új modellje [A new model for price movement in electric power]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 253-274.
    6. Sandro Sapio, 2006. "An Empirically Based Model of the Supply Schedule in Day-Ahead Electricity Markets," LEM Papers Series 2006/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Avci-Surucu, Ezgi & Aydogan, A. Kursat & Akgul, Doganbey, 2016. "Bidding structure, market efficiency and persistence in a multi-time tariff setting," Energy Economics, Elsevier, vol. 54(C), pages 77-87.

    More about this item

    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:prs:recind:rei_0154-3229_2004_num_107_1_3053. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Equipe PERSEE (email available below). General contact details of provider: https://www.persee.fr/collection/rei .

    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.