Adaptive Learning in Financial Markets
We investigate adaptive or evolutionary learning in a repeated version of the Grossman and Stiglitz (1980) model. We demonstrate that any process that is a monotonic selection dynamic will converge to the rational expectations asset demands if the proportion of informed traders is fixed. We also show that these learning processes have a unique asymptotically stable fixed point at the Grossman-Stiglitz (GS) equilibrium. The robustness of learning to noisy experimentation is studied using Binmore and Samuelson's (1999) deterministic drift approximation. Conditions on economic and learning process parameters for adaptive learning to lead to the GS rational expectations equilibrium are presented. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" 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.
Volume (Year): 12 (1999)
Issue (Month): 5 ()
|Contact details of provider:|| Postal: |
Web page: http://www.rfs.oupjournals.org/
More information through EDIRC
|Order Information:||Web: http://www4.oup.co.uk/revfin/subinfo/|
When requesting a correction, please mention this item's handle: RePEc:oup:rfinst:v:12:y:1999:i:5:p:1165-1202. 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: (Oxford University Press)or (Christopher F. Baum)
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.