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Real-time Bayesian learning and bond return predictability
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DOI：10.1016/j.jeconom.2020.04.052.png)
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The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However, such statistical predictability can hardly generate any economic value for investors. Furthermore, we find that strong statistical and economic evidence of bond return predictability from fully-revised macroeconomic data vanishes when real-time macroeconomic information is used. We also show that highly levered investments in bonds can improve short-run bond return predictability. (C) 2021 Elsevier B.V. All rights reserved.
Keyword:
Bayesian learning
Bond return predictability
Non-overlapping bond returns
Parameter uncertainty
Model combinations
Real-time macroeconomic information
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Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks.png)
JOURNAL OF FINANCE
JOURNAL OF FINANCEIF9.5
PREAI
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