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This paper studies whether the evident statistical predictability of bond risk premia translates into economic gains for investors. We propose a novel estimation strategy for affine term structure models that jointly fits yields and bond excess returns, thereby capturing predictive information otherwise hidden to standard estimations. The model predicts excess returns with high regressions R2s and high forecast accuracy but cannot outperform the expectations hypothesis out-of-sample in terms of economic value, showing a general contrast between statistical and economic metrics of forecast evaluation. More specifically, the model mostly generates positive (negative) economic value during times of high (low) macroeconomic uncertainty. Overall, the expectation hypothesis remains a useful benchmark for investment decisions in bond markets, especially in low uncertainty states.
|Additional Information:||© 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Uncontrolled Keywords:||term structure of interest rates; expectations hypothesis; affine models; risk premia; statistical predictability; economic value|
|Subjects:||H Social Sciences > HB Economic Theory|
|Divisions:||Cass Business School > Faculty of Finance|
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