IDEAS home Printed from https://ideas.repec.org/a/prg/jnlefa/v2009y2009i1id63p61-84.html
   My bibliography  Save this article

Unexpected Recovery Risk and LGD Discount Rate Determination

Author

Listed:
  • Jiří Witzany

Abstract

The Basle II parameter called Loss Given Default (LGD) aims to estimate the expected losses on not yet defaulted accounts in the case of default. Banks firstly need to collect historical recovery data, discount the recovery income and cost cash flow to the time of default, and calculate historical recovery rates and LGDs. One of the puzzling tasks is to determine an appropriate discount rate which is very vaguely characterized by the regulation. This paper proposes a market consistent methodology for the LGD discount rate determination based on estimation of the systematic, i.e. undiversifiable, recovery risk and a cost of the risk.

Suggested Citation

  • Jiří Witzany, 2009. "Unexpected Recovery Risk and LGD Discount Rate Determination," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2009(1), pages 61-84.
    • Handle: RePEc:prg:jnlefa:v:2009:y:2009:i:1:id:63:p:61-84
    DOI: 10.18267/j.efaj.63
    as

    Download full text from publisher

    File URL: http://efaj.vse.cz/doi/10.18267/j.efaj.63.html
    Download Restriction: free of charge
    File URL: http://efaj.vse.cz/doi/10.18267/j.efaj.63.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.efaj.63?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. repec:bla:ecnote:v:33:y:2004:i:2:p:183-208 is not listed on IDEAS
    2. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    3. Jon Frye, 2000. "Collateral damage detected," Emerging Issues, Federal Reserve Bank of Chicago, issue Sep.
    4. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.
    5. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Jiří Witzany & Michal Rychnovský & Pavel Charamza, 2012. "Survival Analysis in LGD Modeling," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2012(1), pages 6-27.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ethan Cohen-Cole, 2007. "Asset liquidity, debt valuation and credit risk," Supervisory Research and Analysis Working Papers QAU07-5, Federal Reserve Bank of Boston.
    2. Nicolas Petrosky-Nadeau, 2014. "Credit, Vacancies and Unemployment Fluctuations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(2), pages 191-205, April.
    3. Dermine, J. & Neto de Carvalho, C., 2008. "Bank loan-loss provisioning, central bank rules vs. estimation: The case of Portugal," Journal of Financial Stability, Elsevier, vol. 4(1), pages 1-22, April.
    4. Cangemi, Robert R. & Mason, Joseph R. & Pagano, Michael S., 2012. "Options-based structural model estimation of bond recovery rates," Journal of Financial Intermediation, Elsevier, vol. 21(3), pages 473-506.
    5. Altman, Edward I. & Kalotay, Egon A., 2014. "Ultimate recovery mixtures," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 116-129.
    6. Candian, Giacomo & Dmitriev, Mikhail, 2020. "Default recovery rates and aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    7. Palmroos, Peter, 2009. "Effects of unobserved defaults on correlation between probability of default and loss given on mortgage loans," Research Discussion Papers 3/2009, Bank of Finland.
    8. Thamayanthi Chellathurai, 2017. "Probability Density Of Recovery Rate Given Default Of A Firm’S Debt And Its Constituent Tranches," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
    9. Mora, Nada, 2015. "Creditor recovery: The macroeconomic dependence of industry equilibrium," Journal of Financial Stability, Elsevier, vol. 18(C), pages 172-186.
    10. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
    11. Gürtler, Marc & Hibbeln, Martin, 2013. "Improvements in loss given default forecasts for bank loans," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2354-2366.
    12. Albert Cohen & Nick Costanzino, 2017. "Bond and CDS Pricing via the Stochastic Recovery Black-Cox Model," Risks, MDPI, vol. 5(2), pages 1-28, April.
    13. Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
    14. Chiang, Shu Ling & Yang, Tyler T. & Tsai, Ming Shann, 2016. "Assessing mortgage servicing rights using a reduced-form model: Considering the effects of interest rate risks, prepayment and default risks, and random state variables," Journal of Housing Economics, Elsevier, vol. 32(C), pages 29-46.
    15. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, December.
    16. Carey, Mark & Gordy, Michael B., 2021. "The bank as Grim Reaper: Debt composition and bankruptcy thresholds," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1092-1108.
    17. Alexander Becker & Alexander F. R. Koivusalo & Rudi Schafer, 2012. "Empirical Evidence for the Structural Recovery Model," Papers 1203.3188, arXiv.org.
    18. Sorge, Marco & Virolainen, Kimmo, 2006. "A comparative analysis of macro stress-testing methodologies with application to Finland," Journal of Financial Stability, Elsevier, vol. 2(2), pages 113-151, June.
    19. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    20. Jiri Witzany, 2013. "Estimating Default and Recovery Rate Correlations," Working Papers IES 2013/03, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2013.

    More about this item

    Keywords

    Credit risk; Discount rate; Loss given default; Recovery rate; Regulatory capital;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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

    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:prg:jnlefa:v:2009:y:2009:i:1:id:63:p:61-84. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.html .

    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.