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From Glosten-Milgrom to the whole limit order book and applications to financial regulation

Author

Listed:
  • Weibing Huang

    (LPSM (UMR_8001) - Laboratoire de Probabilités, Statistique et Modélisation - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique - UPCité - Université Paris Cité)

  • Sergio Pulido

    (LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise)

  • Mathieu Rosenbaum

    (CMAP - Centre de Mathématiques Appliquées de l'Ecole polytechnique - Inria - Institut National de Recherche en Informatique et en Automatique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique)

  • Pamela Saliba

    (CMAP - Centre de Mathématiques Appliquées de l'Ecole polytechnique - Inria - Institut National de Recherche en Informatique et en Automatique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique)

  • Emmanouil Sfendourakis

    (CMAP - Centre de Mathématiques Appliquées de l'Ecole polytechnique - Inria - Institut National de Recherche en Informatique et en Automatique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique)

Abstract

We build an agent-based model for the order book with three types of market participants: an informed trader, a noise trader and competitive market makers. Using a Glosten-Milgrom like approach, we are able to deduce the whole limit order book (bid-ask spread and volume available at each price) from the interactions between the different agents. More precisely, we obtain a link between efficient price dynamic, proportion of trades due to the noise trader, traded volume, bid-ask spread and equilibrium limit order book state. With this model, we provide a relevant tool for regulators and market platforms. We show for example that it allows us to forecast consequences of a tick size change on the microstructure of an asset. It also enables us to value quantitatively the queue position of a limit order in the book.

Suggested Citation

  • Weibing Huang & Sergio Pulido & Mathieu Rosenbaum & Pamela Saliba & Emmanouil Sfendourakis, 2025. "From Glosten-Milgrom to the whole limit order book and applications to financial regulation," Working Papers hal-05104768, HAL.
    • Handle: RePEc:hal:wpaper:hal-05104768
    DOI: 10.48550/arXiv.1902.10743
    Note: View the original document on HAL open archive server: https://hal.science/hal-05104768v1
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