A modified fuzzy relational model approach to prediction of Foreign Exchange rates

Foreign Exchange market is the largest and most liquid currency market of international financial market, in which huge amounts of money are gained and lost every minute. This paper presents a modified fuzzy relational model for currency exchange rates forecasting. The performance of this model is compared with several approaches including multi-layer perceptrons, radial basis function neural networks and artificial fuzzy interface systems. All these methods' performances for one-step-ahead predictions are evaluated using real exchange daily rate values of the US Dollar versus Switzerland Franc.