Title :
Modelling and Prediction of the MXNUSD Exchange Rate Using Interval Singleton Type-2 Fuzzy Logic Systems [Application Notes]
Author :
Hernandez Medina, Mdl.A. ; Mendez, Gerardo M.
Abstract :
An IT2 SFLS using hybrid RLS-BP training method was tested and compared for forecasting the daily exchange rate between Mexican Peso and U.S. Dollar (MXNUSD). The results showed that the IT2 SFLS forecaster using RLS-BP hybrid learning provided the best performance, and the base line T1 SFLS provided the worst performance. We conclude, therefore, that it is possible to directly use the daily data of exchange rate to train an IT2 SFLS, in order to predict MXNUSD exchange rate one day in advance. It was observed that IT2 SFLS forecasters efficiently managed the uncertainties presented in the raw historical data
Keywords :
exchange rates; financial data processing; forecasting theory; fuzzy logic; fuzzy systems; knowledge based systems; MXNUSD exchange rate; Mexican Peso; US Dollar; hybrid RLS-BP training method; interval singleton type-2 fuzzy logic systems; Econometrics; Economic forecasting; Environmental economics; Exchange rates; Fuzzy logic; Fuzzy sets; Predictive models; Signal to noise ratio; Testing; Uncertainty;
Journal_Title :
Computational Intelligence Magazine, IEEE
DOI :
10.1109/MCI.2007.357189
