Does Curvature Enhance Forecasting?

International Journal of Theoretical and Applied Finance (IJTAF), 2009

Posted: 16 Jan 2011

Multiple version iconThere are 2 versions of this paper

Date Written: December 1, 2009

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.

Keywords: Parametric term structure models, principal components, vector auto-regressive models, interest rate mean forecasting

Suggested Citation

Almeida, Caio, Does Curvature Enhance Forecasting? (December 1, 2009). International Journal of Theoretical and Applied Finance (IJTAF), 2009, Available at SSRN: https://ssrn.com/abstract=1621473

Caio Almeida (Contact Author)

Princeton University ( email )

26 Prospect Avenue
Princeton, NJ 08540
United States

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