Bond Return Predictability: Economic Value and Links to the Macroeconomy

Antonio Gargano (), Davide Pettenuzzo () and Allan Timmermann ()
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Antonio Gargano: University of Melbourne, Melbourne, Victoria 3010, Australia
Allan Timmermann: Rady School of Management, University of California, San Diego, La Jolla, California 92093

Management Science, 2019, vol. 65, issue 2, 508-540

Abstract: Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such as volatility dynamics and unspanned macro factors. A three-factor model comprising a forward spread, a weighted combination of forward rates, and a macro factor generates notable gains in out-of-sample forecast accuracy compared with a model based on the expectations hypothesis. Such gains in predictive accuracy translate into higher risk-adjusted portfolio returns after accounting for estimation error and model uncertainty. Consistent with models featuring unspanned macro factors, our forecasts of future bond excess returns are strongly negatively correlated with survey forecasts of short rates.

Keywords: bond returns; yield curve; macro factors; stochastic volatility; time-varying parameters; unspanned macro risk factors (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (42)

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https://doi.org/10.1287/mnsc.2017.2829 (application/pdf)

Related works:
Working Paper: Bond Return Predictability: Economic Value and Links to the Macroeconomy (2016)
Working Paper: Bond Return Predictability: Economic Value and Links to the Macroeconomy (2014)
Working Paper: Bond Return Predictability: Economic Value and Links to the Macroeconomy (2014)
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