IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1906.05420.html
   My bibliography  Save this paper

From asymptotic properties of general point processes to the ranking of financial agents

Author

Listed:
  • Othmane Mounjid
  • Mathieu Rosenbaum
  • Pamela Saliba

Abstract

We propose a general non-linear order book model that is built from the individual behaviours of the agents. Our framework encompasses Markovian and Hawkes based models. Under mild assumptions, we prove original results on the ergodicity and diffusivity of such system. Then we provide closed form formulas for various quantities of interest: stationary distribution of the best bid and ask quantities, spread, liquidity fluctuations and price volatility. These formulas are expressed in terms of individual order flows of market participants. Our approach enables us to establish a ranking methodology for the market makers with respect to the quality of their trading.

Suggested Citation

  • Othmane Mounjid & Mathieu Rosenbaum & Pamela Saliba, 2019. "From asymptotic properties of general point processes to the ranking of financial agents," Papers 1906.05420, arXiv.org.
    • Handle: RePEc:arx:papers:1906.05420
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1906.05420
    File Function: Latest version
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luca Mucciante & Alessio Sancetta, 2023. "Estimation of an Order Book Dependent Hawkes Process for Large Datasets," Papers 2307.09077, arXiv.org.
    2. Haeringer, Guillaume & Melton, Hayden, 2020. "High Frequency Fairness," MPRA Paper 103907, University Library of Munich, Germany.
    3. Bastien Baldacci & Dylan Possamai & Mathieu Rosenbaum, 2019. "Optimal make take fees in a multi market maker environment," Papers 1907.11053, arXiv.org, revised Mar 2021.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1906.05420. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.