IDEAS home Printed from https://ideas.repec.org/a/spr/digfin/v6y2024i2d10.1007_s42521-023-00101-0.html
   My bibliography  Save this article

Automated market makers: mean-variance analysis of LPs payoffs and design of pricing functions

Author

Listed:
  • Philippe Bergault

    (Université Paris Dauphine-PSL)

  • Louis Bertucci

    (Institut Louis Bachelier)

  • David Bouba

    (Swaap Labs)

  • Olivier Guéant

    (Université Paris 1 Panthéon-Sorbonne, Centre d’Economie de la Sorbonne)

Abstract

With the emergence of decentralized finance, new trading mechanisms called automated market makers have appeared. The most popular Automated Market Makers are Constant Function Market Makers. They have been studied both theoretically and empirically. In particular, the concept of impermanent loss has emerged and explains part of the profit and loss of liquidity providers in Constant Function Market Makers. In this paper, we propose another mechanism in which price discovery does not solely rely on liquidity takers but also on an external exchange rate or price oracle. We also propose to compare the different mechanisms from the point of view of liquidity providers by using a mean/variance analysis of their profit and loss compared to that of agents holding assets outside of Automated Market Makers. In particular, inspired by Markowitz’ modern portfolio theory, we manage to obtain an efficient frontier for the performance of liquidity providers in the idealized case of a perfect oracle. Beyond that idealized case, we show that even when the oracle is lagged and in the presence of adverse selection by liquidity takers and systematic arbitrageurs, optimized oracle-based mechanisms perform better than popular Constant Function Market Makers.

Suggested Citation

  • Philippe Bergault & Louis Bertucci & David Bouba & Olivier Guéant, 2024. "Automated market makers: mean-variance analysis of LPs payoffs and design of pricing functions," Digital Finance, Springer, vol. 6(2), pages 225-247, June.
  • Handle: RePEc:spr:digfin:v:6:y:2024:i:2:d:10.1007_s42521-023-00101-0
    DOI: 10.1007/s42521-023-00101-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42521-023-00101-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s42521-023-00101-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Alexander Lipton & Vladimir Lucic & Artur Sepp, 2024. "Unified Approach for Hedging Impermanent Loss of Liquidity Provision," Papers 2407.05146, arXiv.org.

    More about this item

    Keywords

    Automated Market Makers; Cryptocurrencies; DeFi; Oracles; Stochastic optimal control;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E49 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Other
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    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:spr:digfin:v:6:y:2024:i:2:d:10.1007_s42521-023-00101-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.