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Adapting to a Market Shock: Optimal Sequential Market-Making
Sanmay Das · Malik Magdon-Ismail

Wed Dec 10 07:30 PM -- 12:00 AM (PST) @ None #None

We study the profit-maximization problem of a monopolistic market-maker who sets two-sided prices in an asset market. The sequential decision problem is hard to solve because the state space is a function. We demonstrate that the belief state is well approximated by a Gaussian distribution. We prove a key monotonicity property of the Gaussian state update which makes the problem tractable, yielding the first optimal sequential market-making algorithm in an established model. The algorithm leads to a surprising insight: an optimal monopolist can provide more liquidity than perfectly competitive market-makers in periods of extreme uncertainty, because a monopolist is willing to absorb initial losses in order to learn a new valuation rapidly so she can extract higher profits later.

Author Information

Sanmay Das (Rensselaer Polytechnic Institute)
Malik Magdon-Ismail (RPI)

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