Robust Bond Risk Premia

2005

We use information contained in yield spreads to recover investors' ex ante required rates of return on corporate securities, and then use these ex ante returns to study the pricing of risky assets. Differently from the standard approach, our asset pricing tests do not rely on the use of ex post average equity returns as proxies for expected equity returns. We Þnd that: (i) the market beta plays a signiÞcant role in the cross-section of expected equity returns, and its role persists even after size and book-to-market factors are accounted for; (ii) the risk premia associated with size and book-to-market are positive, signiÞcant, and countercyclical; and (iii) there is little evidence on positive momentum proÞts. We also Þnd that systematic risk, as captured by common equity factors, is the main driver of the cross-sectional variation in bond yield spreads.

SSRN Electronic Journal, 2017

This paper provides new evidence on bond risk premia by conditioning the classic Campbell-Shiller regressions on the business cycle. In expansions, we …nd mostly positive intercepts and negative regression slopes, but the results are completely reversed in recessions with negative intercepts and positive regression slopes. We reproduce these coe¢ cients in a term structure model with business cycle dependent loadings in the market price of risk. This model also predicts excess returns in the right direction during expansions and recessions, whereas the Gaussian a¢ ne term structure model predicts excess returns for medium-and long-term bonds with the wrong sign during recessions.

SSRN Electronic Journal, 2017

We predict bond betas conditioning on various macro-…nance variables. We explore di¤erences across long-term government bonds, investment grade corporate bonds, and high yield corporate bonds. We conduct out-of-sample forecasting using the new approach of combining explanatory variables through complete subset regressions (CSR). We consider the robustness of CSR forecasts across the 1-month, 3-month, and 12-month forecasting horizon. The CSR method performs well in predicting bond betas.

Studies in Nonlinear Dynamics & Econometrics, 2019

The return forecasting factor is a linear combination of forward rates that seems to predict 1-year excess bond returns of bond of all maturities better than traditional measures obtained from the yield curve. If this single factor actually captures all the relevant fluctuations in bond risk premia, then it should also summarize all the economically relevant variations in excess returns considering different holding periods. We find that it does not. We conclude that including the return forecasting factor as the main driver of risk premia in a term structure model, as has been suggested, is not supported by the data.

Zeitschrift für die gesamte Versicherungswissenschaft

We study yield spreads between government bonds in the European Monetary Union. This segment of the global fixed income market is of particular importance for insurance companies in Europe. Our empirical research strategy is inspired by Gunay (2020) who has analyzed the relationship between credit and liquidity risk in the United States using Granger causality tests. More specifically, we employ the procedure developed by Toda and Yamamoto (1995) to test for Granger causality among yield spreads in five different member countries of the European Monetary Union (namely Austria, Belgium, France, Italy and Ireland) relative to Germany. We examine interest rate data from bonds with three different maturities (5, 10 and 30 years). Given the importance of long-term bonds as asset class for European life insurers and pension funds, the empirical results from the often ignored market for government bonds with a maturity of 30 years should be of interest. With regard to long-term sovereign d...

2009

This paper uses the factor augmented regression framework to analyze the relation between bond excess returns and the macro economy. Using a panel of 131 monthly macroeconomic time series for the sample 1964:1-2007:12, we estimate 8 static factors by the method of asymptotic principal components. We also use Gibb sampling to estimate dynamic factors from the 131 series reorganized into 8 blocks. Regardless of how the factors are estimated, macroeconomic factors are found to have statistically significant predictive power for excess bond returns. We show how a bias correction to the parameter estimates of factor augmented regressions can be obtained. This bias is numerically trivial in our application. The predictive power of real activity for excess bond returns is robust even after accounting for finite sample inference problems. Forecasts of excess bond returns (or bond risk premia) are countercyclical. This implies that investors are compensated for risks associated with recessions.

The North American Journal of Economics and Finance, 2014

This study examines the relationship between the high-yield bonds market and the stock market and indicates that stock returns lead high-yield bond returns. Specifically, this study further shows that this lead-lag relationship is more solid during bear market periods since a downward trend in the stock market implies a high likelihood of the exercise of the equity put in short position embedded in a high-yield bond at maturity. We also conducted out-of-sample forecast using a VAR model, an AR model and naïve estimation during bear market and non-bear market periods. Our results demonstrate that high-yield bond returns are better predicted by a VAR model that includes past stock returns than by an AR model or naive estimation during bear market periods, but such is not the case during non-bear market periods.

Lecturas de Economía, 2016

In this paper, I formally test for the unspanning properties of liquidity premium risk in the context of a joint Gaussian affine term structure model for zero-coupon U.S. Treasury and TIPS bonds. In the model, the liquidity factor is regarded as an additional factor that does not span the yield curve, but improves the forecast of bond risk premia. I present empirical evidence suggesting that liquidity premium indeed helps to forecast U.S. bond risk premia in spite of not being linearly spanned by the information in the joint yield curve. In addition, I show that the liquidity factor does not affect the dynamics of bonds under the pricing measure, but does affect them under the historical measure. Further, variation in the TIPS liquidity premium predicts the future evolution of the traditional yield curve factors.

The Journal of Finance, 2010

and the NBER. Luca Benzoni is at the Federal Reserve Bank of Chicago, Research Department, 230 S. LaSalle St., Chicago, IL 60604, 312-322-8499, lbenzoni@frbchi.org, and the Carlson School of Management, University of Minnesota. We are grateful to

RePEc: Research Papers in Economics, 2004

In 2004 all publications will carry a motif taken from the €100 banknote.