IDEAS home Printed from https://ideas.repec.org/a/bla/jfinan/v62y2007i6p2835-2863.html
   My bibliography  Save this article

Adaptive Traders and the Design of Financial Markets

Author

Listed:
  • SEBASTIEN POUGET

Abstract

This paper studies a financial market populated by adaptive traders. Learning is modeled following Camerer and Ho (1999). A call market and a Walrasian tatonnement are compared in an environment in which both institutions have the same Nash and competitive equilibrium outcomes. When traders learn via a belief‐based model, equilibrium is discovered in both types of markets. In contrast, when traders learn via a reinforcement‐based model, convergence to equilibrium is achieved in the Walrasian tatonnement but not in the call market. This paper suggests that market mechanisms can be designed to foster traders' learning of equilibrium strategies.

Suggested Citation

  • Sebastien Pouget, 2007. "Adaptive Traders and the Design of Financial Markets," Journal of Finance, American Finance Association, vol. 62(6), pages 2835-2863, December.
  • Handle: RePEc:bla:jfinan:v:62:y:2007:i:6:p:2835-2863
    DOI: 10.1111/j.1540-6261.2007.01294.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1540-6261.2007.01294.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1540-6261.2007.01294.x?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
    ---><---

    Citations

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


    Cited by:

    1. Albert Banal-Estañol & Augusto Rupérez Micola, 2010. "Are Agent-based Simulations Robust? The Wholesale Electricity Trading Case," Working Papers 443, Barcelona School of Economics.
    2. Brice Corgnet & Mark Desantis & David Porter, 2018. "What Makes a Good Trader? On the Role of Intuition and Reflection on Trader Performance," Journal of Finance, American Finance Association, vol. 73(3), pages 1113-1137, June.
    3. Eaves, James & Williams, Jeffrey & Power, Gabriel J., 2016. "Do traders strategically time their pledges during real-world Walrasian auctions?," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 109-118.
    4. Chiarella, Carl & He, Xue-Zhong & Wei, Lijian, 2015. "Learning, information processing and order submission in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 245-268.
    5. Pouget, Sebastien, 2007. "Financial market design and bounded rationality: An experiment," Journal of Financial Markets, Elsevier, vol. 10(3), pages 287-317, August.
    6. He, Zhongzhi (Lawrence), 2023. "A Gradient-based reinforcement learning model of market equilibration," Journal of Economic Dynamics and Control, Elsevier, vol. 152(C).
    7. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    8. He, Xue-Zhong & Lin, Shen, 2022. "Reinforcement Learning Equilibrium in Limit Order Markets," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    9. Banal-Estañol, Albert & Rupérez Micola, Augusto, 2011. "Behavioural simulations in spot electricity markets," European Journal of Operational Research, Elsevier, vol. 214(1), pages 147-159, October.
    10. Adão, Luiz F.S. & Silveira, Douglas & Ely, Regis A. & Cajueiro, Daniel O., 2022. "The impacts of interest rates on banks’ loan portfolio risk-taking," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    11. Barroso, Ricardo Vieira & Lima, Joaquim Ignacio Alves Vasconcellos & Lucchetti, Alexandre Henrique & Cajueiro, Daniel Oliveira, 2016. "Interbank network and regulation policies: an analysis through agent-based simulations with adaptive learning," MPRA Paper 73308, University Library of Munich, Germany.

    More about this item

    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:bla:jfinan:v:62:y:2007:i:6:p:2835-2863. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/afaaaea.html .

    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.