Predicting Individual Corporate Bond Returns

Abstract

This paper finds positive evidence of return predictability and investment gains for individual corporate bonds for an extended period from 1973 to 2017. Our sample consists of both public and private company bond observations. We have implemented multiple machine learning methods and designed a Fama-Macbeth-type predictive performance evaluation. In addition to robust predictability evidence, there are four main findings. First of all, we find the lagged corporate bond market return as the most important predictor, suggesting a short-term market reversal story. Second, this paper concludes that equity information is conditionally redundant for similar public and private company bond performance. Third, a model-forecast-implied long-short strategy delivers 1.48% monthly returns and 1.4% alpha during the last two decades, which substantially drops if we do not consider private company bonds. Finally, the return predictability is mainly due to the cash flow component instead of the discount rate component.

Keywords: Bond Characteristics, Individual Corporate Bonds, Machine Learning, Private Company Bonds, Return Decomposition, Return Predictability

JEL Classification: C1, G1