IDEAS home Printed from https://ideas.repec.org/h/spr/lnechp/978-3-540-70556-7_3.html
   My bibliography  Save this book chapter

Market Behavior Under Zero-Intelligence Trading and Price Awareness

In: Complexity and Artificial Markets

Author

Listed:
  • Lucia Milone

    (University of Venice)

Abstract

This paper studies the consequences on market performance of different behavioral assumptions about agents’ trading strategies (pure zero-intelligence, nice behavior and greedy behavior) and of pre-trade quote disclosure (price awareness). The investigation is conducted according to different criteria, such as efficiency, volume and price dispersion. We can summarize the main results as follow. Nice behavior performs better than greedy behavior with respect to all the performance criteria. Information disclosure increases allocative efficiency under the assumption of nice behavior but is not enough to achieve the same result with greedy traders. In fact, greedy traders perform better in the closed-book scenario in terms both of allocative efficiency and transaction volume. Furthermore, nice traders leads to the same volume of transaction in the open- and in the closed-book scenario, despite to a higher level of allocative efficiency in the former than in the latter; this can be explained (at least partially) by the lower number of intermarginal buyers and sellers that fail to trade under information disclosure. Pure zero-intelligent traders are usually overperformed by both the other kind of agents and both in the open- and in the closed-book scenario.

Suggested Citation

  • Lucia Milone, 2008. "Market Behavior Under Zero-Intelligence Trading and Price Awareness," Lecture Notes in Economics and Mathematical Systems, in: Klaus Schredelseker & Florian Hauser (ed.), Complexity and Artificial Markets, chapter 3, pages 27-37, Springer.
  • Handle: RePEc:spr:lnechp:978-3-540-70556-7_3
    DOI: 10.1007/978-3-540-70556-7_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:lnechp:978-3-540-70556-7_3. 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.