The role of CDS spreads in explaining bond recovery rates

Matteo Barbagli (), Pascal François, Geneviève Gauthier and Frédéric Vrins ()
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Matteo Barbagli: Université catholique de Louvain, LIDAM/LFIN, Belgium
Pascal François: HEC Montréal
Geneviève Gauthier: HEC Montréal
Frédéric Vrins: Université catholique de Louvain, LIDAM/LFIN, Belgium

No 2025001, LIDAM Reprints LFIN from Université catholique de Louvain, Louvain Finance (LFIN)

Abstract: We introduce two novel indices built from CDS market data capturing the level and uncertainty information embedded in credit spreads aggregated by industry, and study their role in predicting bonds recovery rates. Analyzing 613 defaulted U.S. corporate bond issues from 2006 to 2019 and using a beta regression model, we find the cross-sectional mean and approximate entropy of CDS spreads aggregated at the sector level to be important predictors of the recovery rates distributions. In the classical beta regression model, both regressors are statistically significant and enhance the pseudo-R2 by up to 4%. Notably, a forward model selection procedure includes the sector-level regressor before well-known variables such as the bonds’ coupon rate or the American default rate. In addition, our sector-uncertainty regressor is the only significant uncertainty variable. These findings offer valuable insights for improving credit risk assessment methodologies and identifying key risk indicators of recovery rates before running prediction models.

Keywords: Credit risk; Recovery rate; Credit default swap; Corporate bond; Uncertainty (search for similar items in EconPapers)
JEL-codes: G21 G28 G32 (search for similar items in EconPapers)
Pages: 20
Date: 2025-03-03
Note: In: Journal of Banking & Finance, 2025, vol. 174, 107414
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Persistent link: https://EconPapers.repec.org/RePEc:ajf:louvlr:2025001

DOI: 10.1016/j.jbankfin.2025.107414

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