Advanced Search
MyIDEAS: Login to save this paper or follow this series

Building an Artificial Stock Market Populated by Reinforcement-Learning Agents

Contents:

Author Info

  • Tomas Ramanauskas

    ()
    (Bank of Lithuania)

  • Aleksandras Vytautas Rutkauskas

    (Vilnius Gediminas Technical University)

Registered author(s):

    Abstract

    In this paper we propose an artificial stock market model based on interaction of heterogeneous agents whose forward-looking behaviour is driven by the reinforcement learning algorithm combined with some evolutionary selection mechanism. We use the model for the analysis of market self-regulation abilities, market efficiency and determinants of emergent properties of the financial market. Distinctive and novel features of the model include strong emphasis on the economic content of individual decision making, application of the Q-learning algorithm for driving individual behaviour, and rich market setup.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.lb.lt/wp2009_no_6
    File Function: Full text
    Download Restriction: no

    Bibliographic Info

    Paper provided by Bank of Lithuania in its series Bank of Lithuania Working Paper Series with number 6.

    as in new window
    Length: 35 pages
    Date of creation: 04 Sep 2009
    Date of revision:
    Handle: RePEc:lie:wpaper:6

    Contact details of provider:
    Postal: Bank of Lithuania Gedimino pr. 6, LT-01103 Vilnius, Lithuania
    Phone: 22 40 08
    Fax: 22 15 01
    Email:
    Web page: http://www.lbank.lt/
    More information through EDIRC

    Related research

    Keywords: agent-based financial modelling; artificial stock market; complex dynamical system; emergent properties; market efficiency; agent heterogeneity; reinforcement learning;

    Find related papers by JEL classification:

    This paper has been announced in the following NEP Reports:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:lie:wpaper:6. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rasa Pusinskaite).

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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