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This paper investigates how market makers can optimise bid–ask quotes to balance profitability, inventory risk and learning about uncertain order flow. Using Bayesian decision theory, Poisson models and Fisher information, it derives a closed-form information–risk frontier and an optimal-stopping rule for quote experimentation. The theoretical results are supported by exact numerical calculations and Monte Carlo simulations.
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Ashot Tarverdyan (2026) studied this question.
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