DOES CURVATURE ENHANCE FORECASTING?

Caio Almeida (), Romeu Gomes (), André Leite (), Axel Simonsen () and José Vicente ()
Additional contact information
Romeu Gomes: Central Bank of Brazil, Brazil
André Leite: Central Bank of Brazil, Brazil
Axel Simonsen: Graduate School of Economics, Getulio Vargas Foundation, Brazil
José Vicente: Central Bank of Brazil and Faculdades, Ibmec-RJ, Brazil

International Journal of Theoretical and Applied Finance (IJTAF), 2009, vol. 12, issue 08, 1171-1196

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 (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (9)

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Working Paper: Does Curvature Enhance Forecasting? (2007)
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DOI: 10.1142/S0219024909005622

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