FORECASTING EXCHANGE RATE CHANGE BETWEEN USD AND JPY BY USING DYNAMIC ADAPTIVE NEURON-FUZZY LOGIC SYSTEM
Weiping Liu1 Eastern
Connecticut State University, USA.
Foreign exchange rate is a chaotic time series which is consistent with the Mackey-Glass equation. Fuzzy logic is an intelligent computational technique and has good potential in forecasting time-series data. This study uses fuzzy logic to study data of exchange rates and build a dynamic adaptive neuron-fuzzy logic forecasting model. The performance of the model built is compared with an autoregressive model by using the same data set.
Key Words: foreign exchange rate, fuzzy logic, chaotic time series, forecast.
JEL Code: F31, F37.