Source of this article and featured image is Wired Science. Description and key fact are generated by Codevision AI system.
Game theorists reveal how nonresponsive pricing strategies can exploit no-swap-regret algorithms to artificially inflate prices. Researchers Collina and Arunachaleswaran discovered that assigning high probabilities to extreme prices maximizes profits against these algorithms, creating an equilibrium where competitors remain stuck with elevated costs. Their findings challenge assumptions about market fairness, showing collusion-like outcomes without explicit coordination. Regulators face dilemmas in balancing algorithm bans with market functionality, as simple strategies can inadvertently drive prices upward. Ben Brubaker’s analysis highlights the hidden risks of algorithmic decision-making in competitive markets.
Key facts
- Nonresponsive pricing strategies can outperform reactive approaches against no-swap-regret algorithms.
- Optimal strategies assign high probabilities to extreme prices while minimizing lower-range options.
- The pricing equilibrium reached mirrors collusive behavior without direct coordination between parties.
- Regulators struggle to ban algorithms without disrupting market dynamics or consumer access.
- The study underscores algorithmic risks in pricing models that lack human oversight mechanisms.
TAGS:
#algorithmic collusion #game theory #market regulation #no-swap-regret algorithms #pricing strategies
