Identifying Relative-Value Opportunities Across Investment Grade Corporate Bond Issuers

Abstract

This thesis investigates whether investment grade corporate bonds issued by companies in different industries exhibit stable pricing relationships that can create relative-value opportunities. The paper uses TRACE bond trade data and Treasury benchmark yields from 2024 to 2025 to construct a dataset of daily corporate bond spreads. This dataset is then used in the multi-stage empirical model. The first stage is the Johansen cointegration and vector error-correction methods to identify long-run equilibrium relationships. A mean-reversion and half life behavior is then used. The final steps are a two-state regime-switching model and a network mapping model. The results show that there are cross-sector pricing relationships, but these relationships are not universal. Only a meaningful subset of bond pairs that is both economically relevant and statistically compelling display these pricing relationships. The strongest bond pairs form a broader issuer connected network. These findings suggest that cross-sector bond pairs with a stable long-run pricing relationship exist in the investment grade corporate bond market and that these cross-sector relationships are consistent with broader market forces, such as funding conditions and limits to arbitrage.