Does curvature enhance forecastinga?

Caio Almeida, Romeu Gomes, André Leite, Axel Simonsen, José Vicente

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential three-factor Diebold and Li (2006) model is proposed, where a fourth factor captures a second type of curvature. The new factor increases model ability to generate volatility and to capture nonlinearities in the yield curve, leading to a significant improvement of forecasting ability. The model is tested against the original Diebold and Li model and some other benchmarks. Based on a forecasting experiment with Brazilian fixed income data, it obtains significantly lower bias and root mean square errors for most examined maturities, and under three different forecasting horizons. Robustness tests based on two sub-sample analyses partially confirm the favorable results.

Original languageEnglish (US)
Pages (from-to)1171-1196
Number of pages26
JournalInternational Journal of Theoretical and Applied Finance
Volume12
Issue number8
DOIs
StatePublished - Dec 2009
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics, Econometrics and Finance(all)

Keywords

  • Interest rate mean forecasting
  • Parametric term structure models
  • Principal components
  • Vector auto-regressive models

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