Yield Curve Predictability, Regimes, and Macroeconomic Information: A Data-Driven Approach
Francesco Audrino and
Kameliya Filipova ()
University of St. Gallen Department of Economics working paper series 2009 from Department of Economics, University of St. Gallen
Abstract:
We propose an empirical approach to determine the various economic sources driving the US yield curve. We allow the conditional dynamics of the yield at different maturities to change in reaction to past information coming from several relevant predictor variables. We consider both endogenous, yield curve factors and exogenous, macroeconomic factors as predictors in our model, letting the data themselves choose the most important variables. We find clear, different economic patterns in the local dynamics and regime specification of the yields depending on the maturity. Moreover, we present strong empirical evidence for the accuracy of the model in fitting in-sample and predicting out-of-sample the yield curve in comparison to several alternative approaches.
Keywords: Yield curve modeling and forecasting; Macroeconomic variables; Tree-structured models; Threshold regimes; GARCH; Bagging (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 E43 E44 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2009-05
New Economics Papers: this item is included in nep-ecm, nep-fmk and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://ux-tauri.unisg.ch/RePEc/usg/dp2009/DP-0910-Au.pdf (application/pdf)
Related works:
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:usg:dp2009:2009-10
Access Statistics for this paper
More papers in University of St. Gallen Department of Economics working paper series 2009 from Department of Economics, University of St. Gallen Contact information at EDIRC.
Bibliographic data for series maintained by Martina Flockerzi ().