Computing corporate bond returns: a word (or two) of caution

Andreani, M, Palhares, D and Richardson, S A (2023) Computing corporate bond returns: a word (or two) of caution. Review of Accounting Studies. ISSN 1380-6653 (In Press) OPEN ACCESS

Abstract

We offer several suggestions for researchers using corporate bond return data. First, despite clear instructions from older papers (e.g., Bessembinder et al., The Review of Financial Studies 22:4219–4258, 2009) about ways to compute credit excess returns, a lot of recent research simply subtracts a Treasury Bill return. We show that this imprecision is likely to contaminate inferences, as the rate component of returns is negatively correlated to the spread component. This is a problem for all research looking at corporate bond returns, especially time series analysis and safer corporate bonds (e.g., investment grade). We provide a simple approach using Wharton Research Data Services (WRDS) data to remove the interest rate component of corporate bond returns. Second, we note significant differences in the coverage of corporate bonds across the Trade Reporting and Compliance Engine (TRACE) platform and typical corporate bond indices. We provide some simple rules for researchers who are using TRACE to select a subset of bonds closest to those contained inside corporate bond indices used by institutional investors. Third, we note differential quality in the prices and hence returns between TRACE and typical corporate bond indices. Corporate bond returns provided by corporate bond indices (i) correctly estimate credit excess returns, (ii) are synchronous for the entire set of bonds, allowing for consistent cross-sectional comparability, and (iii) suffer less from stale pricing issues. Due to these coverage and data quality issues, researchers should try, where possible, to source return data from multiple sources to ensure the robustness of their results.

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Item Type: Article
Subject Areas: Accounting
Date Deposited: 27 Sep 2023 13:35
Date of first compliant deposit: 27 Sep 2023
Last Modified: 28 Feb 2024 02:18
URI: https://lbsresearch.london.edu/id/eprint/3528
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