 Forecasting the term structure of government bond yields in unstable environmentsJoseph Byrne, Shuo Cao and Dimitris Korobilis Journal of Empirical Finance, 2017, vol. 44, issue C, 209-225 Abstract: In this paper we model and predict the term structure of US interest rates in a data-rich and unstable environment. The dynamic Nelson–Siegel factor model is extended to allow the model dimension and the parameters to change over time, in order to account for both model uncertainty and sudden structural changes in one setting. The proposed specification performs better than several alternatives, since it incorporates additional macro-finance information during hard times, while it allows for more parsimonious models to be relevant during normal periods. A dynamic variance decomposition measure constructed from our model shows that parameter uncertainty and model uncertainty regarding different choices of predictors explain a large proportion of the predictive variance of bond yields. Keywords: Term structure of interest rates; Nelson–Siegel; Dynamic model averaging; Bayesian methods; Term premia (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:44:y:2017:i:c:p:209-225 DOI: 10.1016/j.jempfin.2017.09.004 Access Statistics for this article Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff More articles in Journal of Empirical Finance from Elsevier |
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