Forecasting Exchange Rate Change Between USD And JPY By Using Dynamic Adaptive Neuron-Fuzzy Logic System

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 paper 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. Foreign exchange market is the largest and most liquid financial market. Foreign currencies are special financial assets and exchange rates are important financial indicators in the international financial market.