Does Curvature Enhance Forecasting?
International Journal of Theoretical and Applied Finance (IJTAF), 2009
Posted: 16 Jan 2011
Date Written: December 1, 2009
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
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