Artículos de revistas
A Differential Evolution Algorithm For Yield Curve Estimation
Registro en:
Mathematics And Computers In Simulation. Elsevier Science Bv, v. 129, p. 10 - 30, 2016.
0378-4754
1872-7166
WOS:000381534900002
10.1016/j.matcom.2016.04.004
Autor
Maciel
Leandro; Gomide
Fernando; Ballini
Rosangela
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Modeling the term structure of government bond yields is of great interest to macroeconomists and financial market practitioners. It is crucial for bonds and derivatives pricing, risk management, and reveals market expectations, which is essential for monetary policy decisions. This paper suggests the use of a differential evolutionary algorithm to estimate yield curves for US Treasury bonds. It considers parsimonious modeling to avoid non-convergence and high instability of traditional optimization algorithms when estimating model parameters caused by the choice of their initial values during curve fitting. In this approach, the whole yield curve for different maturities is obtained by models parameters estimates. Computational experiments show that the differential evolutionary algorithm provides more accurate yield curves than the ones derived by nonlinear least squares and genetic algorithm approaches. (C) 2016 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. 129 10 30 Research Foundation of the State of Sao Paulo (FAPESP) Brazilian National Research Council (CNPq) Brazilian Ministry of Education (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)