Evolving fuzzy modelling for yield curve forecasting

Leandro Maciel, Rosangela Ballini and Fernando Gomide

International Journal of Economics and Business Research, 2018, vol. 15, issue 3, 290-311

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.

Keywords: evolving fuzzy systems; yield curve; rule-based models; interest rate; adaptive systems. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.inderscience.com/link.php?id=91047 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijecbr:v:15:y:2018:i:3:p:290-311

Access Statistics for this article

More articles in International Journal of Economics and Business Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().