Do different uncertainty indices affect the returns of U.S. corporate bonds?

Abstract

We aim to research how different measures of uncertainties affect U.S. corporate bond returns. We do this by using US corporate bond data and performing beta estimation and rolling window regressions of different uncertainty indices from Bloom (n.d) and Chen et al. (2023), creating factor sensitivities. We perform Fama MacBeth cross-sectional regression and Univariate portfolio regressions to obtain risk premiums and benchmark alphas. We expect that some indices will have a more significant impact on corporate bond returns due to some characteristics being more sensitive to certain types of uncertainty, and we aim to uncover such patterns in our research. Our empirical analysis shows that the uncertainty indices with the most impact are global, world, and monetary policy uncertainty, where monetary policy uncertainty is based on ten major papers. From testing our data across market conditions and bond attributes, we found that these are mainly not robust. The implications of our findings would impact various market participants, including investors, portfolio managers, and policymakers, on how to hedge during times of uncertainty. It will contribute to the literature on corporate bond dynamics and uncertainty.