EconPapers    
Economics at your fingertips  
 

Predicting Bond Return Predictability

Daniel Borup, Jonas Nygaard Eriksen, Mads M. Kjær () and Martin Thyrsgaard ()
Additional contact information
Mads M. Kjær: Department of Economics and Business Economics, Aarhus University, 8210 Aarhus V, Denmark; Danish Finance Institute, 2000 Frederiksberg, Denmark
Martin Thyrsgaard: InCommodities A/S, 8200 Aarhus N, Denmark

Management Science, 2024, vol. 70, issue 2, 931-951

Abstract: This paper provides empirical evidence on predictable time variations in out-of-sample bond return predictability. Bond return predictability is associated with periods of high (low) economic activity (uncertainty), which implies that violations of the expectations hypothesis are state dependent and linked to features of the business cycle. These state dependencies in predictability, established by introducing a new multivariate test for equal conditional predictive ability, can be used in real time to improve out-of-sample bond risk premia estimates and investors’ economic utility through a novel dynamic forecast combination scheme that uses predicted forecasting performance to identify the best set of methods to include in the combined forecast. Dynamically combined forecasts exhibit strong countercyclical behavior and peak during recessions.

Keywords: bond excess returns; forecast combination; state dependencies; multivariate test; equal conditional predictive ability (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2023.4713 (application/pdf)

Related works:
Working Paper: Predicting bond return predictability (2020) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:70:y:2024:i:2:p:931-951

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().

 
Page updated 2025-03-19
Handle: RePEc:inm:ormnsc:v:70:y:2024:i:2:p:931-951