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Limits to arbitrage in electricity markets: A case study of MISO

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  • Birge, John R.
  • Hortaçsu, Ali
  • Mercadal, Ignacia
  • Pavlin, J. Michael

Abstract

We study the case of financial traders in the Midwest electricity market, where they are expected to arbitrage price differences that result in inefficiencies. Using exogenous variation in financial trading from the financial crisis and a period of high transaction costs, we show speculators had only a weak effect. Moreover, while arbitrage was restricted by transaction costs imposed by regulation, some financial players bet in exactly the opposite direction of the pricing gap, sustaining large losses while doing so. We show this is consistent with price manipulation intended to increase the value of a related instrument that bets on local price differences (FTRs).

Suggested Citation

  • Birge, John R. & Hortaçsu, Ali & Mercadal, Ignacia & Pavlin, J. Michael, 2018. "Limits to arbitrage in electricity markets: A case study of MISO," Energy Economics, Elsevier, vol. 75(C), pages 518-533.
    • Handle: RePEc:eee:eneeco:v:75:y:2018:i:c:p:518-533
    DOI: 10.1016/j.eneco.2018.08.024
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    Cited by:

    1. David BENATIA & Etienne BILLETTE de VILLEMEUR, 2019. "Strategic Reneging in Sequential Imperfect Markets," Working Papers 2019-19, Center for Research in Economics and Statistics.
    2. Leslie, Gordon W., 2021. "Who benefits from ratepayer-funded auctions of transmission congestion contracts? Evidence from New York," Energy Economics, Elsevier, vol. 93(C).
    3. Ren, Kezheng & Liu, Jun & Liu, Xinglei & Nie, Yongxin, 2023. "Reinforcement Learning-Based Bi-Level strategic bidding model of Gas-fired unit in integrated electricity and natural gas markets preventing market manipulation," Applied Energy, Elsevier, vol. 336(C).
    4. Zhou Fang, 2023. "Electricity Virtual Bidding Strategy Via Entropy-Regularized Stochastic Control Method," Papers 2303.02303, arXiv.org.
    5. Zhang, Anthony Lee, 2022. "Competition and manipulation in derivative contract markets," Journal of Financial Economics, Elsevier, vol. 144(2), pages 396-413.
    6. Ehsan Samani & Mahdi Kohansal & Hamed Mohsenian-Rad, 2021. "A Data-Driven Convergence Bidding Strategy Based on Reverse Engineering of Market Participants' Performance: A Case of California ISO," Papers 2109.09238, arXiv.org.
    7. Van Moer, Geert, 2019. "Electricity market competition when forward contracts are pairwise efficient," MPRA Paper 96660, University Library of Munich, Germany.
    8. Anna Schwele & Christos Ordoudis & Pierre Pinson & Jalal Kazempour, 2021. "Coordination of power and natural gas markets via financial instruments," Computational Management Science, Springer, vol. 18(4), pages 505-538, October.
    9. Hopkins, Caroline A., 2020. "Convergence bids and market manipulation in the California electricity market," Energy Economics, Elsevier, vol. 89(C).
    10. Mayyas, Ahmad & Chadly, Assia & Amer, Saed Talib & Azar, Elie, 2022. "Economics of the Li-ion batteries and reversible fuel cells as energy storage systems when coupled with dynamic electricity pricing schemes," Energy, Elsevier, vol. 239(PA).
    11. Guo, Nongchao & Lo Prete, Chiara, 2019. "Cross-product manipulation with intertemporal constraints: An equilibrium model," Energy Policy, Elsevier, vol. 134(C).

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    More about this item

    Keywords

    Virtual traders; Financial transmission rights; Wholesale electricity markets; Financial traders; Market manipulation;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • G1 - Financial Economics - - General Financial Markets
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L9 - Industrial Organization - - Industry Studies: Transportation and Utilities

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