We test the out-of-sample predictive power for one-year bond excess returns for a vari- ety 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%.
- Return Predictability,
- Cochrane and Piazzesi
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