US Treasury Yields Research Articles

Risk Characteristics of Emerging Market Bonds

In 2009, emerging market bonds were among the top-performing assets in comparison to both the global equity and fixed income asset classes. The recent, rapid rise in US Treasury yields and the concern over tightening monetary policies in certain countries led us to evaluate the relationship between global interest rate risks and emerging market bonds. In this publication, we attempt to address this relationship with an emphasis on the risk characteristics of the market, along with the historical relationship of emerging market bonds with US Treasuries, other developed market sovereign bonds, and equity market volatility. We consider possible warning signals of impending volatility in emerging market bonds during the period we observed, as well as possible ways to have improved the diversification benefits with equities during this period.

Level, Slope, Curvature: Characterising the Yield Curve in a Cointegrated VAR Model

AbstractEmpirical evidence on the expectations hypothesis of the term structure is in-conclusive and its validity widely debated. Using a cointegrated VAR model of US treasury yields, this paper extends a common approach to test the theory. If, as we find, spreads between two yields are non-stationary, the expectations hypothesis fails. However, we present evidence thatdifferencesbetween two spreads are stationary. This suggests that the curvature of the yield curve may be a more meaningful indicator of expected future interest rates than the slope. Furthermore, we characterise level and slope by deriving the common trends inherent in the cointegrated VAR, and establish feedback patterns between them and the macroeconomy.

Level, Slope, Curvature: Characterising the Yield Curve in a Cointegrated VAR Model

Empirical evidence on the expectations hypothesis of the term structure is in-conclusive and its validity widely debated. Using a cointegrated VAR model of US treasury yields, this paper extends a common approach to test the theory. If, as we find, spreads between two yields are non-stationary, the expectations hypothesis fails. However, we present evidence that differences between two spreads are stationary. This suggests that the curvature of the yield curve may be a more meaningful indicator of expected future interest rates than the slope. Furthermore, we characterise level and slope by deriving the common trends inherent in the cointegrated VAR, and establish feedback patterns between them and the macroeconomy. --

Macro Factors in the Term Structure of Credit Spreads

We estimate arbitrage-free term structure models of US Treasury yields and spreads on BBB and Brated corporate bonds in a doubly-stochastic intensity-based framework. A novel feature of our analysis is the inclusion of macroeconomic variables - indicators of real activity, inflation and financial conditions - as well as latent factors, as drivers of term structure dynamics. Our results point to three key roles played by macro factors in the term structure of spreads: they have a significant impact on the level, and particularly the slope, of the curves; they are largely responsible for variation in the prices of systematic risk; and speculative grade spreads exhibit greater sensitivity to macro shocks than high grade spreads. In addition to estimating risk-neutral default intensities, we provide estimates of physical default intensities using data on Moody's KMV EDFs™ as a forward-looking proxy for default risk. We find that the real and financial activity indicators, along with filtered estimates of the latent factors from our term structure model, explain a large portion of the variation in EDFs™ across time. Furthermore, measures of the price of default event risk implied by estimates of physical and risk-neutral intensities indicate that compensation for default event risk is countercyclical, varies widely across the cycle, and is higher on average and more variable for higher-rated bonds.

Nonlinear term structure dependence: Copula functions, empirics, and risk implications

This paper documents nonlinear cross-sectional dependence in the term structure of US-Treasury yields and points out risk management implications. The analysis is based on a Kalman filter estimation of a two-factor affine model which specifies the yield curve dynamics. We then apply a broad class of copula functions for modeling dependence in factors spanning the yield curve. Our sample of monthly yields in the 1982–2001 period provides evidence of upper tail dependence in yield innovations; i.e., large positive interest rate shocks tend to occur under increased dependence. In contrast, the best-fitting copula model coincides with zero lower tail dependence. This asymmetry has substantial risk management implications. We give an example in estimating bond portfolio loss quantiles and report the biases which result from an application of the normal dependence model.