The Corporate Bond Factor Replication Crisis

TL;DR

This paper uncovers a replication crisis in corporate bond factor research caused by measurement errors and biased filtering, demonstrating many previously identified factors lack statistical significance after correction.

Contribution

It introduces an open source framework with error correction and bias adjustment methods, revealing that most prior factors do not produce significant alphas.

Findings

Most documented factors lose significance after correction.

Measurement errors inflate factor premia.

Open source tools enable reproducible bond research.

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.