The Corporate Bond Factor Replication Crisis

2026-04-09

AI Summary

This study addresses the replication crisis in corporate bond factor research, which stems from measurement errors in transaction prices—inducing variable mismeasurement—and look-ahead bias in post-hoc return sorting. The authors develop a unified framework that systematically identifies and corrects these biases using error-adjusted TRACE data, a bond-specific CAPM model, and rigorous statistical testing. For the first time, they uncover the primary drivers behind inflated factor premia, propose a reproducible correction methodology, and release the full dataset and analytical toolkit. After applying these corrections, the vast majority of 108 tested factors no longer generate statistically significant alphas, substantially revising the prevailing understanding of factor efficacy in the corporate bond market.

Abstract

Corporate bond factor research faces a replication crisis. The crisis stems from two sources that inflate reported factor premia: transaction prices whose measurement error enters both sorting signals and return denominators, creating a correlated errors-in-variables bias, and asymmetric ex-post return filtering that embeds future information into factor construction. Applying our framework to a 'factor zoo' of 108 signals across nine thematic clusters, we show that the majority of previously documented factors do not produce statistically significant bond CAPM alphas after correction. We provide an open source framework via Open Bond Asset Pricing, including error-corrected TRACE data, bias corrected factors, and software for reproducible research.

Problem

• replication crisis
• corporate bond factors
• measurement error
• future information bias
• factor premia

Innovation

• errors-in-variables bias
• ex-post return filtering
• bond factor replication
• TRACE data correction
• reproducible research