Publication
Interest rate prediction: a neuro-hybrid approach with data preprocessing
Nijat Mehdiyev; David Enke
In: International Journal of General Systems, Vol. 43, No. 5, Pages 535-550, Taylor and Francis, 2014.
Abstract
The following research implements a differential evolution-based fuzzy-type clustering method with a fuzzy inference neural network after input preprocessing with regression analysis in order to predict future interest rates, particularly 3-month T-bill rates. The empirical results of the proposed model is compared against nonparametric models, such as locally weighted regression and least squares support vector machines, along with two linear benchmark models, the autoregressive model and the random walk model. The root mean square error is reported for comparison.