Learning Dynamics in an Artificial Currency Market
This paper considers the behavior of the exchange rate in a very simple artificial currency market with two currencies and artificial agents who evolve their forecast rules over time via a genetic algorithm. I consider two simple forecast rules, one linear and the other non-linear. Under the first rule, learning tends to be rapid and complete. Under the second, learning can generate persistent exchange rate dynamics.
|Date of creation:||01 Apr 2001|
|Contact details of provider:|| Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sce:scecf1:31. 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: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.