Algorithmic Collusion in Electronic Markets: The Impact of Tick Size
Álvaro Cartea, Patrick Chang, José Penalva
This papers shows that machine learning algorithms can tacitly collude during market making to extract rents and that the tick size matters: a large tick size obstructs competition, while a smaller tick size lowers trading costs for liquidity takers, but slows the speed of convergence to an equilibrium.
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