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Statistical Arbitrage and Information Flow in an Electricity Balancing Market

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  • Derek W. Bunn and Stefan O.E. Kermer

Abstract

Motivated by the events following a natural experiment in 2015, when the market rules for electricity spot trading were changed in Britain, we analyse the operational effects of market participants responding to price incentives for spillage and shortage positions in a single price, real-time market. We develop an analytical model for optimal real-time decisions by generators and speculators based upon forecasts of the conditional distribution of the total system imbalance between instantaneous supply and demand. From this, we examine the effects of time delays in information transparency for the consequent statistical arbitrage positions. We backtested this model empirically to the Austrian system imbalance settlements process within the German/Austrian integrated market. Results suggest that permitting additional intraday flexibility from a physical generator or a non-physical trader can be beneficial for the agents themselves, the system operator and market efficiency.

Suggested Citation

  • Derek W. Bunn and Stefan O.E. Kermer, 2021. "Statistical Arbitrage and Information Flow in an Electricity Balancing Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    • Handle: RePEc:aen:journl:ej42-5-bunn
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    Cited by:

    1. Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
    2. Sinan Deng & John Inekwe & Vladimir Smirnov & Andrew Wait & Chao Wang, 2023. "Machine Learning and Deep Learning Forecasts of Electricity Imbalance Prices," Working Papers 2023-03, University of Sydney, School of Economics.
    3. Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.

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    JEL classification:

    • F0 - International Economics - - General

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