IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1203.2287.html
   My bibliography  Save this paper

Bounds for rating override rates

Author

Listed:
  • Dirk Tasche

Abstract

Overrides of credit ratings are important correctives of ratings that are determined by statistical rating models. Financial institutions and banking regulators agree on this because on the one hand errors with ratings of corporates or banks can have fatal consequences for the lending institutions and on the other hand errors by statistical methods can be minimised but not completely avoided. Nonetheless, rating overrides can be misused in order to conceal the real riskiness of borrowers or even entire portfolios. That is why rating overrides usually are strictly governed and carefully recorded. It is not clear, however, which frequency of overrides is appropriate for a given rating model within a predefined time period. This paper argues that there is a natural error rate associated with a statistical rating model that may be used to inform assessment of whether or not an observed override rate is adequate. The natural error rate is closely related to the rating model's discriminatory power and can readily be calculated.

Suggested Citation

  • Dirk Tasche, 2012. "Bounds for rating override rates," Papers 1203.2287, arXiv.org, revised Aug 2012.
    • Handle: RePEc:arx:papers:1203.2287
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1203.2287
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dirk Tasche, 2009. "Estimating discriminatory power and PD curves when the number of defaults is small," Papers 0905.3928, arXiv.org, revised Mar 2010.
    2. Cramer,J. S., 2011. "Logit Models from Economics and Other Fields," Cambridge Books, Cambridge University Press, number 9780521188036.
    3. Dirk Tasche, 2006. "Validation of internal rating systems and PD estimates," Papers physics/0606071, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    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. Dirk Tasche, 2012. "The art of probability-of-default curve calibration," Papers 1212.3716, arXiv.org, revised Nov 2013.
    2. Szabó, György & Borsos, István & Szombati, Edit, 2019. "Games, graphs and Kirchhoff laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 416-423.
    3. Wosnitza, Jan Henrik, 2022. "Calibration alternatives to logistic regression and their potential for transferring the dispersion of discriminatory power into uncertainties of probabilities of default," Discussion Papers 04/2022, Deutsche Bundesbank.
    4. Marcin Chlebus, 2014. "One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 37.
    5. Katarzyna Sokołowska, 2014. "Determinants and perceptions of social mobility in Poland, 1992-2008," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 8(1), March.
    6. Bianca Polenzani & Chiara Riganelli & Andrea Marchini, 2020. "Sustainability Perception of Local Extra Virgin Olive Oil and Consumers’ Attitude: A New Italian Perspective," Sustainability, MDPI, vol. 12(3), pages 1-18, January.
    7. Dirk Tasche, 2015. "Fitting a distribution to Value-at-Risk and Expected Shortfall, with an application to covered bonds," Papers 1505.07484, arXiv.org, revised Nov 2015.
    8. Annemiek Vuren & Daniel Vuuren, 2007. "Financial Incentives in Disability Insurance in the Netherlands," De Economist, Springer, vol. 155(1), pages 73-98, March.
    9. Gordon Kemp & João Santos Silva, 2016. "Partial effects in fixed-effects models," United Kingdom Stata Users' Group Meetings 2016 06, Stata Users Group.
    10. Aldona Standar & Agnieszka Kozera & Łukasz Satoła, 2021. "The Importance of Local Investments Co-Financed by the European Union in the Field of Renewable Energy Sources in Rural Areas of Poland," Energies, MDPI, vol. 14(2), pages 1-23, January.
    11. Zigraiova, Diana & Jakubik, Petr, 2015. "Systemic event prediction by an aggregate early warning system: An application to the Czech Republic," Economic Systems, Elsevier, vol. 39(4), pages 553-576.
    12. Morone, Marco & Cornaglia, Anna, 2010. "An econometric model to quantify benchmark downturn LGD on residential mortgages," MPRA Paper 25588, University Library of Munich, Germany.
    13. Fioretti, Guido, 2007. "The organizational learning curve," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1375-1384, March.
    14. François Coppens & Fernando Gonzáles & Gerhard Winkler, 2007. "The performance of credit rating systems in the assessment of collateral used in Eurosystem monetary policy operations," Working Paper Research 118, National Bank of Belgium.
    15. Giuseppe Orlando & Roberta Pelosi, 2020. "Non-Performing Loans for Italian Companies: When Time Matters. An Empirical Research on Estimating Probability to Default and Loss Given Default," IJFS, MDPI, vol. 8(4), pages 1-22, November.
    16. Beare, Brendan K & Toda, Alexis Akira, 2020. "On the emergence of a power law in the distribution of COVID-19 cases," University of California at San Diego, Economics Working Paper Series qt9k5027d0, Department of Economics, UC San Diego.
    17. Trinh, Thoai Quang & Rañola, Roberto F. & Camacho, Leni D. & Simelton, Elisabeth, 2018. "Determinants of farmers’ adaptation to climate change in agricultural production in the central region of Vietnam," Land Use Policy, Elsevier, vol. 70(C), pages 224-231.
    18. Karacuka, Mehmet & Çatık, A. Nazif & Haucap, Justus, 2013. "Consumer choice and local network effects in mobile telecommunications in Turkey," Telecommunications Policy, Elsevier, vol. 37(4), pages 334-344.
    19. Diana Zigraiova & Petr Jakubik, 2014. "Systemic Event Prediction by Early Warning System," Working Papers IES 2014/01, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2014.
    20. Tasche, Dirk, 2013. "Bayesian estimation of probabilities of default for low default portfolios," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 6(3), pages 302-326, July.

    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:arx:papers:1203.2287. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.