IDEAS home Printed from https://ideas.repec.org/a/cup/jfinqa/v53y2018i06p2619-2661_00.html
   My bibliography  Save this article

The Term Structure of Expected Recovery Rates

Author

Listed:
  • Doshi, Hitesh
  • Elkamhi, Redouane
  • Ornthanalai, Chayawat

Abstract

There is widespread agreement that corporate debts’ recovery rates are time varying, but empirical work in this area is limited. We show that the joint information from the term structure of senior and subordinate credit default swaps can identify the level and the dynamics of recovery rates. We estimate a reduced-form no-arbitrage model on 46 firms across different industries. We find that the term structure of expected recovery rates is, on average, downward sloping. However, an inversion occurs during the 2008 crisis, suggesting the market expects higher recoveries conditional on short-term survival. The inversion is more pronounced for firms in distressed industries.

Suggested Citation

  • Doshi, Hitesh & Elkamhi, Redouane & Ornthanalai, Chayawat, 2018. "The Term Structure of Expected Recovery Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(6), pages 2619-2661, December.
    • Handle: RePEc:cup:jfinqa:v:53:y:2018:i:06:p:2619-2661_00
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0022109018000558/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nazemi, Abdolreza & Rezazadeh, Hani & Fabozzi, Frank J. & Höchstötter, Markus, 2022. "Deep learning for modeling the collection rate for third-party buyers," International Journal of Forecasting, Elsevier, vol. 38(1), pages 240-252.
    2. Bo Young Chang & Greg Orosi, 2020. "A Simple Method for Extracting the Probability of Default from American Put Option Prices," Staff Working Papers 20-15, Bank of Canada.
    3. Jean‐François Bégin & Mathieu Boudreault & Mathieu Thériault, 2024. "Leveraging prices from credit and equity option markets for portfolio risk management," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 122-147, January.
    4. Nazemi, Abdolreza & Baumann, Friedrich & Fabozzi, Frank J., 2022. "Intertemporal defaulted bond recoveries prediction via machine learning," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1162-1177.
    5. Pascal François, 2019. "The Determinants of Market-Implied Recovery Rates," Risks, MDPI, vol. 7(2), pages 1-15, May.
    6. Jansen, Jeroen & Das, Sanjiv R. & Fabozzi, Frank J., 2018. "Local volatility and the recovery rate of credit default swaps," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 1-29.
    7. Masahiko Egami & Rusudan Kevkhishvili, 2020. "Post-Last Exit Time Process and its Application to Loss-Given-Default Distribution," Papers 2009.00868, arXiv.org, revised Mar 2024.
    8. Barbagli, Matteo & François, Pascal & Gauthier, Geneviève & Vrins, Frédéric, 2024. "The role of CDS spreads in explaining bond recovery rates," LIDAM Discussion Papers LFIN 2024002, Université catholique de Louvain, Louvain Finance (LFIN).
    9. Andrea Gamba & Alessio Saretto, 2020. "Growth Options and Credit Risk," Management Science, INFORMS, vol. 66(9), pages 4269-4291, September.
    10. Kellner, Ralf & Nagl, Maximilian & Rösch, Daniel, 2022. "Opening the black box – Quantile neural networks for loss given default prediction," Journal of Banking & Finance, Elsevier, vol. 134(C).
    11. Bo Young Chang & Greg Orosi, 2020. "A simple method for extracting the probability of default from American put option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1535-1547, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cup:jfinqa:v:53:y:2018:i:06:p:2619-2661_00. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/jfq .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.