Please use this identifier to cite or link to this item:
Type: Artigo
Title: Evolving fuzzy modelling for yield curve forecasting
Author: Maciel, Leandro
Ballini, Rosangela
Gomide, Fernando
Abstract: Forecasting the term structure of interest rates plays a crucial role in portfolio management, household finance decisions, business investment planning, and policy formulation. This paper aims to address yield curve forecasting and evolving fuzzy systems modelling using data from US and Brazilian fixed income markets. Evolving fuzzy models provide a high level of system adaptation and learn the system dynamic continuously, which is essential for uncertain environments as interest rate markets. Computational experiments show that the evolving fuzzy modelling approaches describe the interest rate behaviour accurately, outperforming traditional econometric techniques in terms of error measures and statistical tests. Moreover, evolving models provide promising results for short and long-term maturities and for both fixed income markets evaluated, highlighting its potential to forecast complex nonlinear dynamics in uncertain environments
Subject: Sistemas fuzzy
Taxas de juros
Country: Reino Unido
Editor: Inderscience
Rights: Fechado
Identifier DOI: 10.1504/IJEBR.2018.091047
Date Issue: 2018
Appears in Collections:FEEC - Artigos e Outros Documentos
IE - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.