Neural network pruning applied to real exchange rate analysis

Abstract

AbstractNeural 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‐à‐vis the US dollar at the introduction of the Euro on 1 January 1999. Copyright © 2002 John Wiley & Sons, Ltd.