Measuring Contagion in the South‐East Asian Economic Crisis: An Exploration Using Artificial Neural Networks

Abstract

An artificial neural network methodology is used to develop a new measure of contagion using exchange rate data from the Asian Crisis of 1997 and beyond. Connection weight changes during retraining of networks used to forecast exchange rates form the basis of this measure. These weight changes are used in obtaining a contribution factor for independent variables used in a forecasting process. Volatilities of contribution factors form the basis of the measure of contagion obtained. These volatilities are statistically validated through a series of simulations where critical values for them are derived. The measures of contagion obtained are then matched to concurrent economic and financial shocks that occurred during the crisis. It is found that there is good correlation between these events and the contagion measures obtained.