Quantifying Informational Illiquidity in Corporate Bond Markets
A structural credit-risk model explains corporate bond pricing, liquidity costs, and adverse selection under information asymmetry in secondary markets.
What it examines
This study develops a structural credit-risk model combining information asymmetry, adverse selection, and liquidity frictions to explain corporate bond trading behavior. Using analytical tools and calibration with empirical turnover and yield spread data, it aims to quantify informational illiquidity and its impact on bond prices.
What it concludes
The model demonstrates that information asymmetry significantly affects bond yields and trading volumes, especially for high-risk bonds. These results inform policies for bond market liquidity, risk management, and regulation. Future research may refine friction modeling and broaden the study's applicability in financial markets.
Evidence objects
Researchers unveil a new credit-risk model merging corporate bond pricing, liquidity, and information asymmetry, revealing adverse selection drives yield discounts: $$0.51%$$--$$1.14%$$ for investment-grade and $$2.11%$$--$$3.62%$$ for speculative-grade bonds with precision.
key_findings bullet 1 · key_findings · validation V0
Surprisingly, the model predicts a hump-and-rebound, non-monotonic relationship between trading volume and yield spreads, closely matching empirical US bond trade data by enabling costly liquidity-status revelations that mitigate adverse selection.
key_findings bullet 2 · key_findings · validation V0
Its major contribution lies in integrating informational and non-informational trading frictions, defining liquidity-status strategies, decomposing liquidity costs, and calibrating historical data, while acknowledging model limitations from parameter assumptions robustly tested.
key_findings bullet 3 · key_findings · validation V0
The paper innovatively merges informational and non-informational frictions in corporate bond pricing, providing a refined yield spread decomposition. Its original integration fills a literature gap, employing a robust modeling approach calibrated with empirical data. This novel perspective enhances fixed income research, clearly transformative, making the findings particularly compelling and significant.
key_findings bullet 4 · key_findings · validation V0
Raw abstract and provenance
- … Motivated by this observation, we develop a structural credit-risk model in which the secondary bond market suffers from information asymmetry among bond investors. …
Source row: 1626 · abstract type: snippet