Abstract Covariances between aggregate stock returns and changes in bond yields change sign over time. Existing theories emphasize either time-varying properties of expected inflation or time-varying properties of real yields. Using revisions in survey forecasts as proxies for macroeconomic news, neither approach succeeds empirically. Inflation-centric models require much more news about expected future inflation than we observe from surveys. Real-centric models posit signs of covariances among macroeconomic news, changes in yields, and stock returns that do not match those in the data. In a nutshell, macroeconomic news appears to drive a substantial part of stock–bond comovement, but not in ways consistent with our theories.

A combination of observed and unobserved (latent) factors capture term structure dynamics. Information about these dynamics is extracted from observed factors using restrictions implied by no-arbitrage, without specifying or estimating any of the parameters associated with latent factors. Estimation is equivalent to fitting the moment conditions of a set of regressions, where no-arbitrage imposes cross-equation restrictions on the coefficients. The methodology is applied to the dynamics of inflation and yields. Outside of the disinflationary period of 1979 through 1983, short-term rates move one-for-one with expected inflation, while bond risk premia are insensitive to inflation.

Standard approaches to building and estimating dynamic term structure models rely on the assumption that yields can serve as the factors. However, the assumption is neither theoretically necessary nor empirically supported. This article documents that almost half of the variation in bond risk premia cannot be detected using the cross-section of yields. Fluctuations in this hidden component have strong forecast power for both future short-term interest rates and excess bond returns. They are also negatively correlated with aggregate economic activity, but macroeconomic variables explain only a small fraction of variation in the hidden factor. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

[Standard approaches to building and estimating dynamic term structure models rely on the assumption that yields can serve as the factors. However, the assumption is neither theoretically necessary nor empirically supported. This article documents that almost half of the variation in bond risk premia cannot be detected using the cross-section of yields. Fluctuations in this hidden component have strong forecast power for both future short-term interest rates and excess bond returns. They are also negatively correlated with aggregate economic activity, but macroeconomic variables explain only a small fraction of variation in the hidden factor.]

[A firm's instantaneous probability of default is modeled as a translated square-root diffusion process modified to allow the process to be correlated with default-free interest rates. The parameters of the process are estimated for 161 firms. An extended Kalman filter approach is used that incorporates both the time-series and cross-sectional (term structure) properties of the individual firms' bond prices. The model is reasonably successful at fitting corporate bond yields, while key features of the term structures of yield spreads are captured in the signs and magnitudes of the resulting parameter estimates.]

A firm's instantaneous probability of default is modeled as a translated square-root diffusion process modified to allow the process to be correlated with default-free interest rates. The parameters of the process are estimated for 161 firms. An extended Kalman filter approach is used that incorporates both the time-series and cross-sectional (term structure) properties of the individual firms' bond prices. The model is reasonably successful at fitting corporate bond yields, while key features of the term structures of yield spreads are captured in the signs and magnitudes of the resulting parameter estimates.

ABSTRACT Revisions in successive Greenbook forecasts of quarterly real GDP growth proxy for news of current and expected future economic growth. In the sample 1975 through 2015, news of future growth is slightly negatively related to contemporaneous changes in Treasury bond yields, while news of current growth is strongly positively related to changes in these yields. Both results are difficult to reconcile with a representative agent's bondholding first‐order condition. A continuous‐time dynamic model of output attributes almost all of the covariation with yields to martingale innovations in log output and a minimal amount to innovations in the conditional drift of log output.

ABSTRACT Shocks to nominal bond yields consist of news about expected future inflation, expected future real short rates, and expected excess returns—all over the bond's life. I estimate the magnitude of the first component for short‐ and long‐maturity Treasury bonds. At a quarterly frequency, variances of news about expected inflation account for between 10% to 20% of variances of yield shocks. Standard dynamic models with long‐run risk imply variance ratios close to 1. Habit formation models fare somewhat better. The magnitudes of shocks to real rates and expected excess returns cannot be determined reliably.

ABSTRACT The conditional covariance between aggregate stock returns and aggregate consumption growth varies substantially over time. When stock market wealth is high relative to consumption, both the conditional covariance and correlation are high. This pattern is consistent with the “composition effect,” where agents' consumption growth is more closely tied to stock returns when stock wealth is a larger share of total wealth. This variation can be used to test asset‐pricing models in which the price of consumption risk varies. After accounting for variations in this price, the relation between expected excess stock returns and the conditional covariance is negative.