Shared Bidding Algorithms and Competition: Evidence from Electricity Markets

2026-07-14

AI Summary

This study investigates whether the sharing of third-party automated bidding algorithms leads electricity market participants to internalize each other’s profits and thereby attenuate competition. Leveraging five-minute granular battery bidding data from Australia’s National Electricity Market and exploiting regulatory changes in disclosure requirements, the authors employ dynamic storage valuation, counterfactual bid re-clearing, and high-frequency structural behavioral identification to demonstrate—for the first time—that coordination at the algorithm provider level can generate substantial anticompetitive effects. When batteries managed by the same algorithm provider account for over 30% of near-marginal capacity, bidding behavior becomes significantly synchronized, resulting in average annual consumer welfare losses of $5.5 million. Firms also demonstrably sacrifice their own profits to bolster rivals using the same provider—an effect undetectable by conventional market concentration metrics based on asset ownership.

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 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.

Problem

• algorithmic collusion
• shared bidding algorithms
• electricity markets
• profit internalization
• market competition

Innovation

• shared bidding algorithms
• algorithmic collusion
• electricity markets
• dynamic arbitrage
• counterfactual market reclearing