IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-540-33087-5_6.html
   My bibliography  Save this book chapter

A Multi-Factor Approach for Systematic Default and Recovery Risk

In: The Basel II Risk Parameters

Author

Listed:
  • Daniel Rösch

    (University of Regensburg)

  • Harald Scheule

    (University of Melbourne)

Abstract

The following article develops a simultaneous multi-factor model for defaults and recoveries. Applying this model, risk parameters can be forecast using systematic and idiosyncratic risk factors and their implied correlations. The theoretical framework is accompanied by an empirical analysis in which a negative correlation between defaults and recoveries over the business cycle is observed. In the study, default and recovery rates are modeled by business cycle indicators and the properties of the economic and regulatory capital given these risk drivers are shown.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Daniel Rösch & Harald Scheule, 2006. "A Multi-Factor Approach for Systematic Default and Recovery Risk," Springer Books, in: Bernd Engelmann & Robert Rauhmeier (ed.), The Basel II Risk Parameters, chapter 0, pages 105-125, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-33087-5_6
    DOI: 10.1007/3-540-33087-9_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Li, Hui, 2010. "Downturn LGD: A Spot Recovery Approach," MPRA Paper 71986, University Library of Munich, Germany, revised 30 Apr 2013.
    2. Rösch, Daniel & Scheule, Harald, 2012. "Capital incentives and adequacy for securitizations," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 733-748.
    3. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, September.
    4. 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.
    5. Rongda Chen & Ze Wang, 2013. "Curve Fitting of the Corporate Recovery Rates: The Comparison of Beta Distribution Estimation and Kernel Density Estimation," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-9, July.
    6. Schläfer, Timo & Uhrig-Homburg, Marliese, 2014. "Is recovery risk priced?," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 257-270.
    7. Salvatore D. Tomarchio & Antonio Punzo, 2019. "Modelling the loss given default distribution via a family of zero‐and‐one inflated mixture models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1247-1266, October.
    8. Michael Jacobs, 2012. "An empirical study of the returns on defaulted debt," Applied Financial Economics, Taylor & Francis Journals, vol. 22(7), pages 563-579, April.
    9. Li, Hui, 2010. "Downturn LGD: A Spot Recovery Approach," MPRA Paper 20010, University Library of Munich, Germany.
    10. Bellotti, Tony & Crook, Jonathan, 2012. "Loss given default models incorporating macroeconomic variables for credit cards," International Journal of Forecasting, Elsevier, vol. 28(1), pages 171-182.
    11. Daniel Rosch & Harald Scheule, 2008. "Credit Losses in Economic Downturns - Empirical Evidence for Hong Kong Mortgage Loans," Working Papers 152008, Hong Kong Institute for Monetary Research.
    12. Xiaolin Luo & Pavel V. Shevchenko, 2010. "Markov chain Monte Carlo estimation of default and recovery: dependent via the latent systematic factor," Papers 1011.2827, arXiv.org, revised Oct 2014.
    13. Pavel V. Shevchenko & Xiaolin Luo, 2011. "Dependent default and recovery: MCMC study of downturn LGD credit risk model," Papers 1112.5766, arXiv.org.
    14. Huong Dang, 2014. "A Competing Risks Dynamic Hazard Approach to Investigate the Insolvency Outcomes of Property-Casualty Insurers," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 39(1), pages 42-76, January.

    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:spr:sprchp:978-3-540-33087-5_6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.