Machine Learning and the Yield Curve: Tree-Based Macroeconomic Regime Switching

Fuente: arXiv
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Main Authors: Bie, Siyu, Diebold, Francis X., He, Jingyu, Li, Junye
Format: Preprint
Published: 2024
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author Bie, Siyu
Diebold, Francis X.
He, Jingyu
Li, Junye
author_facet Bie, Siyu
Diebold, Francis X.
He, Jingyu
Li, Junye
contents We explore tree-based macroeconomic regime-switching in the context of the dynamic Nelson-Siegel (DNS) yield-curve model. In particular, we customize the tree-growing algorithm to partition macroeconomic variables based on the DNS model's marginal likelihood, thereby identifying regime-shifting patterns in the yield curve. Compared to traditional Markov-switching models, our model offers clear economic interpretation via macroeconomic linkages and ensures computational simplicity. In an empirical application to U.S. Treasury yields, we find (1) important yield-curve regime switching, and (2) evidence that macroeconomic variables have predictive power for the yield curve when the federal funds rate is high, but not in other regimes, thereby refining the notion of yield curve ''macro-spanning''.
format Preprint
id arxiv_https___arxiv_org_abs_2408_12863
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Machine Learning and the Yield Curve: Tree-Based Macroeconomic Regime Switching
Bie, Siyu
Diebold, Francis X.
He, Jingyu
Li, Junye
Econometrics
Applications
We explore tree-based macroeconomic regime-switching in the context of the dynamic Nelson-Siegel (DNS) yield-curve model. In particular, we customize the tree-growing algorithm to partition macroeconomic variables based on the DNS model's marginal likelihood, thereby identifying regime-shifting patterns in the yield curve. Compared to traditional Markov-switching models, our model offers clear economic interpretation via macroeconomic linkages and ensures computational simplicity. In an empirical application to U.S. Treasury yields, we find (1) important yield-curve regime switching, and (2) evidence that macroeconomic variables have predictive power for the yield curve when the federal funds rate is high, but not in other regimes, thereby refining the notion of yield curve ''macro-spanning''.
title Machine Learning and the Yield Curve: Tree-Based Macroeconomic Regime Switching
topic Econometrics
Applications
url https://arxiv.org/abs/2408.12863