ExplorerEnvironmental ScienceEconomics
Research PaperResearchia:202607.15037

Shared Bidding Algorithms and Competition: Evidence from Electricity Markets

Nicolas Eschenbaum

Abstract

Competing firms increasingly delegate pricing and bidding decisions to algorithms supplied by the same third-party providers. We study whether a shared algorithm leads competitors to internalise one another's profits, using data from the Australian National Electricity Market, where every battery's bids are observed at 5-minute frequency and can be linked to an identifiable autobidding provider. Bids constructed by the same provider co-move, and do so more strongly after a disclosure reform made...

Submitted: July 15, 2026Subjects: Economics; Environmental Science

Description / Details

Competing firms increasingly delegate pricing and bidding decisions to algorithms supplied by the same third-party providers. We study whether a shared algorithm leads competitors to internalise one another's profits, using data from the Australian National Electricity Market, where every battery's bids are observed at 5-minute frequency and can be linked to an identifiable autobidding provider. Bids constructed by the same provider co-move, and do so more strongly after a disclosure reform made the common scarcity state easier to observe: the same information that steers batteries towards efficient arbitrage also synchronises the bids of competitors who share a provider. To separate co-movement due to shared information from joint profit maximisation, we estimate each battery's dynamic value of stored energy and reclear the market under counterfactual bids. Owner-level profits cannot rationalise observed bidding: batteries forgo profitable dispatch where it would depress the prices earned by same-provider batteries owned by rival firms, and the estimated weight on those rivals' profits is close to one. We find evidence of this conduct only where a provider's share of near-margin battery capacity exceeds roughly 30%, corresponding to an installed share of roughly 20%. The identified conduct costs consumers an annualised $5.5 million on the current fleet, and it arises at the level of the algorithm provider rather than the asset owner, a layer that ownership-based concentration screens do not capture.


Source: arXiv:2607.13002v1 - http://arxiv.org/abs/2607.13002v1 PDF: https://arxiv.org/pdf/2607.13002v1 Original Link: http://arxiv.org/abs/2607.13002v1

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Submission Info
Date:
Jul 15, 2026
Topic:
Environmental Science
Area:
Economics
Comments:
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