Neural Network Pruning Applied to Real Exchange Rate Analysis
Neural networks are fitted to real exchange rates of several industrialized countries. The size and topology of the networks is found through the use of multiple correlation coefficients, principal component analysis of residuals and graphical analysis of network output per hidden layer cell and input layer cell. These pruned neural networks are good approximations to varying non-linear trends in real exchange rates. Non-linear dynamic analysis shows that the long-term equilibrium values of several European currencies correspond to the actual values within the European Monetary System. Based on its long-term equilibrium value, the Euro appears to be undervalued vis-a-vis the US dollar at the introduction of the Euro on 1 January 1999. Copyright © 2002 by John Wiley & Sons, Ltd.
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): 21 (2002)
Issue (Month): 8 (December)
|Contact details of provider:|| Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 |
When requesting a correction, please mention this item's handle: RePEc:jof:jforec:v:21:y:2002:i:8:p:559-77. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.