IDEAS home Printed from https://ideas.repec.org/p/sce/scecf4/310.html
   My bibliography  Save this paper

From Heterogeneous expectations to exchange rate dynamic:

Author

Listed:
  • Philippe Protin
  • Luc Neuberg
  • Christine Louargant

Abstract

The purpose of this paper is to analyze how heterogeneous behaviors of agents influence the exchange rates dynamic in the short and long terms. We examine how agents use the information and which kind of information, in order to take theirs decisions to form an expectation of the exchange rate. We investigate a methodology based on interactive agents simulations, following the Santa Fe Artificial Stock Market. Each trader is modeled as an autonomous, interactive agent and the aggregation of their behavior results in foreign exchange market dynamic. Genetic algorithm is the tool used to compute agents, and the simulated market tends to replicate the real EUR/USD exchange rate market. We consider six kinds of agents with pure behavior: fundamentalists, positive feedback traders and negative ones, naive traders, news traders (positive and negative). To reproduce stylized facts of the exchange rates dynamic, we conclude that the key factor is the correct proportion of each agents type, whiteout any need of mimetic behaviors, adaptive agents or pure noisy agents

Suggested Citation

  • Philippe Protin & Luc Neuberg & Christine Louargant, 2004. "From Heterogeneous expectations to exchange rate dynamic:," Computing in Economics and Finance 2004 310, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:310
    as

    Download full text from publisher

    File URL: http://repec.org/sce2004/up.21766.1078078186.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    exchange rates dynamic; heterogeneous interactive agents behaviour; genetic algorithm; learning process;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

    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:sce:scecf4:310. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.