Forecasting the Brazilian yield curve using forward-looking variables

Resumo

This paper proposes a forecasting model that combines a factor augmented VAR (FAVAR) methodology with the Nelson and Siegel (NS) parametrization of the yield curve in order to predict the Brazilian term structure of interest rates. Importantly, we extract the principal components for the FAVAR from a large data set containing a range of forward looking macroeconomic and financial variables. Our forecasting model improves on the predictive accuracy of extant models in the literature significantly, particularly at short-term horizons. For instance, the mean absolute forecast errors are 15-40% lower than those of the random walk benchmark on predictions at the three-month horizon. The out of-sample analysis shows that the inclusion of forward-looking indicators is the key to improving the predictive ability of the model. (C) 2016 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Ficha do documento

Tipo

Artigo científico

Ano

2017

Instituição

Elsevier Science Bv

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Acesso aberto

DOI

10.1016/j.ijforecast.2016.08.001

Identificador

oai:repositorio.fgv.br:10438/23679

Temas

EconomiaDados

Palavras-chave

BondsFactor-augmented VARForecastingTerm structureYield curveEconomiaPrevisão - Métodos estatísticosVariáveis (Matemática)