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Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond

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  • Yao, Xiao
  • Crook, Jonathan
  • Andreeva, Galina

Abstract

This study investigates the impacts of unobservable firm heterogeneity on modelling corporate bond recovery rates at the instrument level. Based on the recovery information over a long horizon from 1986 to 2012, we find that an obligor-varying linear factor model presents significant improvements in explaining the variations of recovery rates with a remarkably high intra-class correlation being observed. It emphasizes that the inclusion of an obligor-varying random effect term has effectively explained the unobservable firm level information shared by instruments of the same issuer and thus results in an improvement of predictive accuracy of recovery rates. The empirical results show that the latent economic cyclical effects have been well represented by firm level heterogeneity, and strong evidence is presented for the normal distributional assumption of the recovery rates. Finally, we demonstrate the choice of recovery rate models may influence portfolio risk with the obligor-varying factor model generating a more right clustered loss distribution than other regression methods on the aggregated portfolio.

Suggested Citation

  • Yao, Xiao & Crook, Jonathan & Andreeva, Galina, 2017. "Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond," Journal of Financial Stability, Elsevier, vol. 28(C), pages 1-15.
  • Handle: RePEc:eee:finsta:v:28:y:2017:i:c:p:1-15
    DOI: 10.1016/j.jfs.2016.11.005
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    Cited by:

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    2. Yuanxin Liu & FengYun Li & Xinhua Yu & Jiahai Yuan & Dong Zhou, 2018. "Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China," Sustainability, MDPI, vol. 10(5), pages 1-21, May.
    3. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).
    4. Krüger, Steffen & Rösch, Daniel & Scheule, Harald, 2018. "The impact of loan loss provisioning on bank capital requirements," Journal of Financial Stability, Elsevier, vol. 36(C), pages 114-129.

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    More about this item

    Keywords

    Unobservable heterogeneity; Loss given default; Portfolio loss distribution;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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