IDEAS home Printed from https://ideas.repec.org/a/wly/finmar/v19y2010i1p47-61.html
   My bibliography  Save this article

Through‐the‐Cycle Ratings Versus Point‐in‐Time Ratings and Implications of the Mapping Between Both Rating Types

Author

Listed:
  • Rebekka Topp
  • Robert Perl

Abstract

The two philosophies of ratings, one that includes cyclical effects and the other that doesn't, are mirrored by the two different rating types commonly known as point‐in‐time (pit) and through‐the‐cycle (ttc). Point‐in‐time ratings try to evaluate the current situation of a customer by taking into account both cyclical and permanent effects. In contrast, through the‐cycle ratings focus mainly on the permanent component of default risk and are nearly independent from cyclical changes in the creditworthiness of a customer. In this paper we give a review of the characteristics of both rating types and examine whether these properties can actually be observed in practice. In this context we present the results of an analysis of Standard& Poor's rating data, which show that the ratings, though being through‐the‐cycle, still vary in accordance with the business cycle. Another concern of this paper is the wide spread practice to map ‘external’ through‐the‐cycle ratings to ‘internal’ point‐in‐time ratings, with the purpose to enrich or validate a financial institution's internal rating database. We show that in doing so financial institutions severely misspecify customers' risk profiles and under‐ or overestimate costs in connection with credit pricing or capitalization. We confirm our theoretical considerations by calculating pricing quantities when using one or the other rating information.

Suggested Citation

  • Rebekka Topp & Robert Perl, 2010. "Through‐the‐Cycle Ratings Versus Point‐in‐Time Ratings and Implications of the Mapping Between Both Rating Types," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 19(1), pages 47-61, February.
  • Handle: RePEc:wly:finmar:v:19:y:2010:i:1:p:47-61
    DOI: 10.1111/j.1468-0416.2009.00154.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1468-0416.2009.00154.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1468-0416.2009.00154.x?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
    ---><---

    References listed on IDEAS

    as
    1. André Lucas & Siem Jan Koopman, 2005. "Business and default cycles for credit risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 311-323.
    2. Mark S. Carey & William F. Treacy, 1998. "Credit risk rating at large U.S. banks," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), vol. 84(Nov), pages 897-921, September.
    3. Koopman, Siem Jan & Lucas, Andre & Klaassen, Pieter, 2005. "Empirical credit cycles and capital buffer formation," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3159-3179, December.
    4. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
    5. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
    6. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
    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. Correa, Arnildo & Marins, Jaqueline & Neves, Myrian & da Silva, Antonio Carlos, 2014. "Credit Default and Business Cycles: An Empirical Investigation of Brazilian Retail Loans," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(3), September.
    2. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    3. Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
    4. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," IJFS, MDPI, vol. 2(1), pages 1-22, March.
    5. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
    6. Myriam Ben Ayed & Adel Karaa & Jean‐Luc Prigent, 2018. "Duration Models For Credit Rating Migration: Evidence From The Financial Crisis," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1870-1886, July.
    7. Anisa Caja & Frédéric Planchet, 2014. "Modeling Cycle Dependence in Credit Insurance," Risks, MDPI, vol. 2(1), pages 1-15, March.
    8. Mizen, Paul & Tsoukas, Serafeim, 2012. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," International Journal of Forecasting, Elsevier, vol. 28(1), pages 273-287.
    9. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
    10. 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.
    11. Korolkiewicz, Malgorzata W. & Elliott, Robert J., 2008. "A hidden Markov model of credit quality," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3807-3819, December.
    12. Cifter, Atilla & Yilmazer, Sait & Cifter, Elif, 2009. "Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey," Economic Modelling, Elsevier, vol. 26(6), pages 1382-1388, November.
    13. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    14. Gloy, Brent A. & LaDue, Eddy L. & Gunderson, Michael A., 2004. "Credit Risk Migration Experienced By Agricultural Lenders," Working Papers 127147, Cornell University, Department of Applied Economics and Management.
    15. repec:fgv:epgrbe:v:68:n:3:a:3 is not listed on IDEAS
    16. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.
    17. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    18. Jaehoon Hahn & Ho-Seong Moon, 2016. "Credit Cycle and the Macroeconomy: Empirical Evidence from Korea," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 22(4), pages 76-108, December.
    19. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    20. 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.
    21. Schechtman, Ricardo, 2013. "Default matrices: A complete measurement of banks’ consumer credit delinquency," Journal of Financial Stability, Elsevier, vol. 9(4), pages 460-474.

    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:wly:finmar:v:19:y:2010:i:1:p:47-61. 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: Wiley Content Delivery (email available below). General contact details of provider: .

    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.