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Closed-form approximations in multi-asset market making

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Listed:
  • Philippe Bergault
  • David Evangelista
  • Olivier Gu'eant
  • Douglas Vieira

Abstract

A large proportion of market making models derive from the seminal model of Avellaneda and Stoikov. The numerical approximation of the value function and the optimal quotes in these models remains a challenge when the number of assets is large. In this article, we propose closed-form approximations for the value functions of many multi-asset extensions of the Avellaneda-Stoikov model. These approximations or proxies can be used (i) as heuristic evaluation functions, (ii) as initial value functions in reinforcement learning algorithms, and/or (iii) directly to design quoting strategies through a greedy approach. Regarding the latter, our results lead to new and easily interpretable closed-form approximations for the optimal quotes, both in the finite-horizon case and in the asymptotic (ergodic) regime.

Suggested Citation

  • Philippe Bergault & David Evangelista & Olivier Gu'eant & Douglas Vieira, 2018. "Closed-form approximations in multi-asset market making," Papers 1810.04383, arXiv.org, revised Sep 2022.
    • Handle: RePEc:arx:papers:1810.04383
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    References listed on IDEAS

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    Cited by:

    1. Bastien Baldacci & Jerome Benveniste & Gordon Ritter, 2020. "Optimal trading without optimal control," Papers 2012.12945, arXiv.org.

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