Out-of-Sample Predictability of Bond Returns

23 Pages Posted: 9 Apr 2013

See all articles by Luiz Paulo Fichtner

Luiz Paulo Fichtner

New University of Lisbon - Faculdade de Economia; European Central Bank (ECB)

Pedro Santa-Clara

New University of Lisbon - Nova School of Business and Economics; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

Date Written: December 28, 2012

Abstract

We test the out-of-sample predictive power for one-year bond excess returns for a variety of models that have been proposed in the literature. We find that these models perform well in sample, but have worse out-of-sample performance than the historical sample mean. We write the one-year excess return on a n-maturity bond at time t + 1 as the difference between n times the n-maturity bond yield at time t, and the sum of n − 1 times the (n − 1)-maturity bond yield at time t + 1 and the one-year bond yield at time t. Instead of forecasting returns directly, we forecast bond yields and replace them in the bond ex- cess return definition. We use two bond yield forecasting methods: a random walk and a dynamic Nelson-Siegel approach proposed by Diebold and Li (2006). An investor who used a simple random walk on yields would have predicted bond excess returns with out-of-sample R-squares of up to 15%, while a dynamic Nelson-Siegel approach would have produced out-of-sample R-squares of up to 30%.

JEL Classification: G1, E4

Suggested Citation

Fichtner, Luiz Paulo and Santa-Clara, Pedro, Out-of-Sample Predictability of Bond Returns (December 28, 2012). Available at SSRN: https://ssrn.com/abstract=2226169 or http://dx.doi.org/10.2139/ssrn.2226169

Luiz Paulo Fichtner (Contact Author)

New University of Lisbon - Faculdade de Economia ( email )

Campus de Campolide
Lisboa, 1099-032
Portugal

European Central Bank (ECB) ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

Pedro Santa-Clara

New University of Lisbon - Nova School of Business and Economics ( email )

Lisbon
Portugal

HOME PAGE: http://docentes.fe.unl.pt/~psc/

National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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