Fuzzy ARIMA model for forecasting the foreign exchange market

Abstract

Considering the time-series ARTMA (p,d,q) model and fuzzy regression model, this paper develops a fuzzy ARIMA (FARIMA) model and applies it to forecasting the exchange rate of NT dollars to US dollars. This model includes interval models with interval parameters and the possibility distribution of future values is provided by FARIMA. This model makes it possible for decision makers to forecast the best- and worst-possible situations based on fewer observations than the ARIMA model. (C) 2001 Elsevier Science B.V. All rights reserved.