IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/14711.html
   My bibliography  Save this paper

Rating philosophy and dynamic properties of internal rating systems: A general framework and an application to backtesting

Author

Listed:
  • Cornaglia, Anna
  • Morone, Marco

Abstract

The paper draws a general framework for asset and default dynamics, separating the influence of the economic cycle into a component which is embedded in the rating system and an unobservable risk factor that determines the movements of defaults around the ex ante estimated PDs. The two components – the sensitivity of ratings to credit cycle and conditional asset correlation - can be quantified through a Maximum Likelihood approach, giving a measure of the cyclicality of the rating system, and allowing for a number of applications: among those the modified binomial test proposed here.

Suggested Citation

  • Cornaglia, Anna & Morone, Marco, 2009. "Rating philosophy and dynamic properties of internal rating systems: A general framework and an application to backtesting," MPRA Paper 14711, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:14711
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/14711/1/MPRA_paper_14711.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    2. Daniel Roesch & Harald Scheule, 2007. "Stress-testing credit risk parameters: An application to retail loan portfolios," Published Paper Series 2007-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    3. repec:uts:ppaper:v:1:y:2007:i:1:p:55-75 is not listed on IDEAS
    4. Dirk Tasche, 2006. "Validation of internal rating systems and PD estimates," Papers physics/0606071, arXiv.org.
    5. Petr Jakubík, 2006. "Does Credit Risk Vary with Economic Cycles? The Case of Finland," Working Papers IES 2006/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2006.
    6. 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.
    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. Blümke, Oliver, 2018. "On the cyclicality of default rates of banks: A comparative study of the asset correlation and diversification effects," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 65-77.
    2. Sokolov, Yuri, 2010. "Business cycle effects on portfolio credit risk: A simple FX Adjustment for a factor model," MPRA Paper 27222, University Library of Munich, Germany.
    3. D. Th. Vezeris & C. J. Schinas & Th. S. Kyrgos & V. A. Bizergianidou & I. P. Karkanis, 2020. "Optimization of Backtesting Techniques in Automated High Frequency Trading Systems Using the d-Backtest PS Method," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 975-1054, December.
    4. Michael Kalkbrener & Akwum Onwunta, 2009. "Validating Structural Credit Portfolio Models," Working Papers 014, COMISEF.
    5. Michael Kalkbrener & Natalie Packham, 2024. "A Markov approach to credit rating migration conditional on economic states," Papers 2403.14868, arXiv.org.

    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. 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.
    2. 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.
    3. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    4. Gatfaoui Hayette, 2004. "Idiosyncratic Risk, Systematic Risk and Stochastic Volatility: An Implementation of Merton’s Credit Risk Valuation," Finance 0404004, University Library of Munich, Germany.
    5. Jones, Stewart & Johnstone, David & Wilson, Roy, 2015. "An empirical evaluation of the performance of binary classifiers in the prediction of credit ratings changes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 72-85.
    6. Chiara Pederzoli & Costanza Torricelli & Dimitrios Tsomocos, 2010. "Rating systems, procyclicality and Basel II: an evaluation in a general equilibrium framework," Annals of Finance, Springer, vol. 6(1), pages 33-49, January.
    7. Johannes Hörner & Nicolas S Lambert, 2021. "Motivational Ratings [Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1892-1935.
    8. Chew Lian Chua & G. C. Lim & Penelope Smith, 2008. "A Bayesian Simulation Approach to Inference on a Multi-State Latent Factor Intensity Model," Melbourne Institute Working Paper Series wp2008n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    9. 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.
    10. Gagliardini, P. & Gourieroux, C., 2005. "Migration correlation: Definition and efficient estimation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 865-894, April.
    11. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    12. 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.
    13. Salvador, Carlos & Pastor, Jose Manuel & Fernández de Guevara, Juan, 2014. "Impact of the subprime crisis on bank ratings: The effect of the hardening of rating policies and worsening of solvency," Journal of Financial Stability, Elsevier, vol. 11(C), pages 13-31.
    14. Smith, Brent C, 2011. "Stability in consumer credit scores: Level and direction of FICO score drift as a precursor to mortgage default and prepayment," Journal of Housing Economics, Elsevier, vol. 20(4), pages 285-298.
    15. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "On sovereign credit migration: A study of alternative estimators and rating dynamics," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3448-3469, April.
    16. , L., 2013. "Fragility of reputation and clustering of risk-taking," Theoretical Economics, Econometric Society, vol. 8(3), September.
    17. 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.
    18. Cesaroni, Tatiana, 2015. "Procyclicality of credit rating systems: How to manage it," Journal of Economics and Business, Elsevier, vol. 82(C), pages 62-83.
    19. Liuren Wu & Frank Xiaoling Zhang, 2008. "A No-Arbitrage Analysis of Macroeconomic Determinants of the Credit Spread Term Structure," Management Science, INFORMS, vol. 54(6), pages 1160-1175, June.
    20. Bertrand Rime, 2007. "Could Regional and Cantonal Banks Reduce Credit Risk through National Diversification?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 143(I), pages 49-65, March.

    More about this item

    Keywords

    rating philosophy; rating dynamics; cyclicality; asset correlation; migration matrices; ML estimation; backtesting; binomial test;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:pra:mprapa:14711. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.