IDEAS home Printed from https://ideas.repec.org/p/ecl/corcae/06-08.html
   My bibliography  Save this paper

Default Estimation for Low-Default Portfolios

Author

Listed:
  • Kiefer, Nicholas M.

    (Cornell U and US Department of the Treasury)

Abstract

The problem in default probability estimation for low-default portfolios is that there is little relevant historical data information. No amount of data processing can fix this problem. More information is required. Incorporating expert opinion formally is an attractive option.

Suggested Citation

  • Kiefer, Nicholas M., 2006. "Default Estimation for Low-Default Portfolios," Working Papers 06-08, Cornell University, Center for Analytic Economics.
  • Handle: RePEc:ecl:corcae:06-08
    as

    Download full text from publisher

    File URL: https://cae.economics.cornell.edu/06-08.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Garthwaite, Paul H. & Kadane, Joseph B. & O'Hagan, Anthony, 2005. "Statistical Methods for Eliciting Probability Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 680-701, June.
    2. Stefan Weber & Kay Giesecke, 2003. "Credit Contagion and Aggregate Losses," Computing in Economics and Finance 2003 246, Society for Computational Economics.
    3. Giesecke, Kay & Weber, Stefan, 2004. "Cyclical correlations, credit contagion, and portfolio losses," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 3009-3036, December.
    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. Dalla Valle, Luciana & De Giuli, Maria Elena & Tarantola, Claudia & Manelli, Claudio, 2016. "Default probability estimation via pair copula constructions," European Journal of Operational Research, Elsevier, vol. 249(1), pages 298-311.
    2. Dirk Tasche, 2011. "Bayesian estimation of probabilities of default for low default portfolios," Papers 1112.5550, arXiv.org, revised Aug 2013.
    3. Tsukahara, Fábio Yasuhiro & Kimura, Herbert & Sobreiro, Vinicius Amorim & Zambrano, Juan Carlos Arismendi, 2016. "Validation of default probability models: A stress testing approach," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 70-85.
    4. Orth, Walter, 2011. "Default probability estimation in small samples: With an application to sovereign bonds," Discussion Papers in Econometrics and Statistics 5/11, University of Cologne, Institute of Econometrics and Statistics.
    5. Yi-Ping Chang & Chih-Tun Yu, 2014. "Bayesian confidence intervals for probability of default and asset correlation of portfolio credit risk," Computational Statistics, Springer, vol. 29(1), pages 331-361, February.
    6. Kiefer, Nicholas M., 2009. "Incentive-Compatible Elicitation of Quantiles," Working Papers 09-13, Cornell University, Center for Analytic Economics.
    7. Feixue Huang & Yan He, 2010. "Enactment of Default Point in KMV Model on CMBC, SPDB, CMB, Huaxia Bank and SDB," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 1(1), pages 30-36, December.
    8. Wei, Li & Yuan, Zhongyi, 2016. "The loss given default of a low-default portfolio with weak contagion," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 113-123.
    9. Orth, Walter, 2011. "Default probability estimation in small samples - with an application to sovereign bonds," MPRA Paper 33778, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:ecl:corcae:06-08. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/cacorus.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.