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The Review of Asset Pricing Studies Vol. 14 No. 3 2024

Decomposing Uncertainty in Macro-Finance Term Structure Models

Joseph P. Byrne1; Shuo Cao2

1 University of Strathclyde , UK · 2 Shenzhen Stock Exchange , China

Abstract

This paper studies the extent to which macro-finance term structure models are susceptible to predictive uncertainty. We propose a general form of arbitrage-free models and quantify the relative importance of unpredictable priced risk variance, as well as macro-finance model uncertainty and learning uncertainty in predictability. Predictive performance and relative contributions of uncertainty sources are dynamically measured based on Bayesian methods, revealing dominating priced risk variance and other important uncertainty sources at different points in time. Macro-finance model uncertainty is high for near-term forward spread forecasts and contributes up to 87% of predictive uncertainty prior to recessions, implying strong dispersion in the information content of macro variables when forming near-term monetary policy expectations.

DOI
10.1093/rapstu/raae004
Volume
14
Issue
3
Pages
428-449
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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