IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v36y2012i5p1464-1477.html
   My bibliography  Save this article

Granularity adjustment for default risk factor model with cohorts

Author

Listed:
  • Gourieroux, C.
  • Jasiak, J.

Abstract

This paper examines granularity adjustments to parameter estimators in a default risk model with cohorts. The model is an extension of the Vasicek model (Vasicek, 1991) and includes a general factor and cohort specific factors. The granularity adjustments derived in the paper concern the mean and/or the variance of observed default frequencies and are easy to implement in practice. For illustration, the method is applied to the S&P corporate ratings. The Granularity Adjusted (GA) estimators are compared to the unadjusted estimators in terms of their asymptotic properties and in finite sample.

Suggested Citation

  • Gourieroux, C. & Jasiak, J., 2012. "Granularity adjustment for default risk factor model with cohorts," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1464-1477.
  • Handle: RePEc:eee:jbfina:v:36:y:2012:i:5:p:1464-1477
    DOI: 10.1016/j.jbankfin.2011.12.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037842661100358X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbankfin.2011.12.013?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. Lütkebohmert, Eva & Gordy, Michael B., 2007. "Granularity adjustment for Basel II," Discussion Paper Series 2: Banking and Financial Studies 2007,01, Deutsche Bundesbank.
    2. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
    3. Patrick Gagliardini, 2005. "Stochastic Migration Models with Application to Corporate Risk," Journal of Financial Econometrics, Oxford University Press, vol. 3(2), pages 188-226.
    4. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    5. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    6. Feng, D. & Gourieroux, C. & Jasiak, J., 2008. "The ordered qualitative model for credit rating transitions," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 111-130, January.
    7. Dirk Tasche, 2005. "Measuring sectoral diversification in an asymptotic multi-factor framework," Papers physics/0505142, arXiv.org, revised Jul 2006.
    8. Nikola Tarashev & Haibin Zhu, 2008. "Specification and Calibration Errors in Measures of Portfolio Credit Risk: The Case of the ASRF Model," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 129-173, June.
    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. Gordy, Michael B. & Marrone, James, 2012. "Granularity adjustment for mark-to-market credit risk models," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1896-1910.

    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. Tarashev, Nikola, 2010. "Measuring portfolio credit risk correctly: Why parameter uncertainty matters," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2065-2076, September.
    2. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    3. Alain Monfort & Jean-Paul Renne, 2013. "Default, Liquidity, and Crises: an Econometric Framework," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 221-262, March.
    4. Kao, Lie-Jane, 2015. "A portfolio-invariant capital allocation scheme penalizing concentration risk," Economic Modelling, Elsevier, vol. 51(C), pages 560-570.
    5. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Rating transitions forecasting: a filtering approach," Post-Print hal-03347521, HAL.
    6. Areski Cousin & J'er^ome Lelong & Tom Picard, 2021. "Rating transitions forecasting: a filtering approach," Papers 2109.10567, arXiv.org, revised Jun 2023.
    7. Mager, Ferdinand & Schmieder, Christian, 2008. "Stress testing of real credit portfolios," Discussion Paper Series 2: Banking and Financial Studies 2008,17, Deutsche Bundesbank.
    8. Daniel Rösch & Harald Scheule, 2014. "Forecasting Mortgage Securitization Risk Under Systematic Risk and Parameter Uncertainty," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 563-586, September.
    9. Areski Cousin & Jérôme Lelong & Tom Picard, 2022. "Rating transitions forecasting: a filtering approach," Working Papers hal-03347521, HAL.
    10. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    11. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    12. Patrick Gagliardini & Christian Gouriéroux, 2011. "Approximate Derivative Pricing for Large Classes of Homogeneous Assets with Systematic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 237-280, Spring.
    13. Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
    14. Wolff, Christian & Bams, Dennis & Pisa, Magdalena, 2015. "Credit risk characteristics of US small business portfolios," CEPR Discussion Papers 10889, C.E.P.R. Discussion Papers.
    15. Mora, Nada, 2015. "Creditor recovery: The macroeconomic dependence of industry equilibrium," Journal of Financial Stability, Elsevier, vol. 18(C), pages 172-186.
    16. Klaus Duellmann & Jonathan Küll & Michael Kunisch, 2010. "Estimating asset correlations from stock prices or default rates - which method is superior?," Post-Print hal-00736734, HAL.
    17. 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.
    18. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    19. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2012. "Assessing the systemic risk of a heterogeneous portfolio of banks during the recent financial crisis," Journal of Financial Stability, Elsevier, vol. 8(3), pages 193-205.
    20. Liuren Wu & Frank X. Zhang, 2005. "A no-arbitrage analysis of economic determinants of the credit spread term structure," Finance and Economics Discussion Series 2005-59, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    Factor model; Granularity adjustment; Systematic risk; Idiosyncratic risk;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

    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:eee:jbfina:v:36:y:2012:i:5:p:1464-1477. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbf .

    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.