A New Approach to Modeling Early Warning Systems for Currency Crises : can a machine-learning fuzzy expert system predict the currency crises effectively?

This paper presents a hybrid model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning abil i ty of neural network with the inference mechanism of fuzzy logic . The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis . Significantly, the model can also construct a rel iable causal relationship among the variables through the obtained knowledge base. Compared to the tradit ionally used techniques such as logit , the proposed model can thus lead to a somewhat more prescriptive modeling approach towards finding ways to prevent currency crises.