Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/210736 
Year of Publication: 
2019
Series/Report no.: 
Staff Report No. 884
Publisher: 
Federal Reserve Bank of New York, New York, NY
Abstract: 
We investigate the factor structure of the term structure of interest rates and argue that characterizing the minimal dimension of the data-generating process is more challenging than currently appreciated. To circumvent these difficulties, we introduce a novel nonparametric bootstrap that is robust to general forms of time and cross-sectional dependence and conditional heteroskedasticity of unknown form. We show that our bootstrap procedure is asymptotically valid and exhibits excellent finite-sample properties in simulations. We demonstrate the applicability of our results in two empirical exercises: First, we show that measures of equity market tail risk and the state of the macroeconomy predict bond returns beyond the level or slope of the yield curve; second, we provide a bootstrap-based bias correction and confidence intervals for the probability of recession based on the shape of the yield curve. Our results apply more generally to all assets with a finite maturity structure.
Subjects: 
term structure of interest rates
factor models
principal components
bond risk premiums
resampling-based inference
JEL: 
C15
C58
G10
G12
Document Type: 
Working Paper

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