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Procyclicality of credit rating systems: how to manage it

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  • Tatiana Cesaroni

    (Bank of Italy)

Abstract

This paper evaluates the characteristics of a Point in Time (PiT) rating approach for the estimation of firms’ credit risk in terms of procyclicality. To this end I first estimate a logit model for the probability default (PD) of a set of Italian non-financial firms during the period 2006-2012, then, in order to address the issue of rating stability (hedging against rating changes) during the financial crisis, I study the effectiveness of ex post smoothing of PDs in terms of obligors’ migration among rating risk grades. As a by-product I further discuss and analyse the role played by the choice of rating scale in producing ratings stability. The results show that ex post PD smoothing is able to remove business cycle effects on the credit risk estimates and to produce a mitigation of obligors’ migration among risk grades over time. The rating scale choice also has a significant impact on rating stability. These findings have important policy implications in banking sector practices in terms of the stability of the financial system.

Suggested Citation

  • Tatiana Cesaroni, 2015. "Procyclicality of credit rating systems: how to manage it," Temi di discussione (Economic working papers) 1034, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_1034_15
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    References listed on IDEAS

    as
    1. Cesaroni, Tatiana & Maccini, Louis & Malgarini, Marco, 2011. "Business cycle stylized facts and inventory behaviour: New evidence for the Euro area," International Journal of Production Economics, Elsevier, vol. 133(1), pages 12-24, September.
    2. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    3. Philip Lowe, 2002. "Credit risk measurement and procyclicality," BIS Working Papers 116, Bank for International Settlements.
    4. C. H. Furfine & Jeffery D. Amato, 2003. "Are credit ratings procyclical?," BIS Working Papers 129, Bank for International Settlements.
    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. Loffler, Gunter, 2004. "An anatomy of rating through the cycle," Journal of Banking & Finance, Elsevier, vol. 28(3), pages 695-720, March.
    7. Mr. John Kiff & Michael Kisser & Miss Liliana B Schumacher, 2013. "Rating Through-the-Cycle: What does the Concept Imply for Rating Stability and Accuracy?," IMF Working Papers 2013/064, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Auria, Laura & Bingmer, Markus & Graciano, Carlos Mateo Caicedo & Charavel, Clémence & Gavilá, Sergio & Iannamorelli, Alessandra & Levy, Aviram & Maldonado, Alfredo & Resch, Florian & Rossi, Anna Mari, 2021. "Overview of central banks’ in-house credit assessment systems in the euro area," Occasional Paper Series 284, European Central Bank.
    2. Patrycja Chodnicka Jaworska, "undated". "Prediction Of Banking Sector Condition," Review of Socio - Economic Perspectives 201703, Reviewsep.
    3. Roulet, Caroline, 2018. "Basel III: Effects of capital and liquidity regulations on European bank lending," Journal of Economics and Business, Elsevier, vol. 95(C), pages 26-46.
    4. Laura Auria & Markus Bingmer & Carlos Mateo Caicedo Graciano & Clémence Charavel & Sergio Gavilá & Alessandra Iannamorelli & Aviram Levy & Alfredo Maldonado & Florian Resch & Anna Maria Rossi & Step, 2021. "Overview of central banks’ in-house credit assessment systems in the euro area," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems) 13, Bank of Italy, Directorate General for Markets and Payment System.
    5. Lukasz Prorokowski, 2022. "New definition of default," Bank i Kredyt, Narodowy Bank Polski, vol. 53(5), pages 523-564.
    6. Michael Jacobs, 2021. "Validation of Corporate Probability of Default Models Considering Alternative Use Cases," IJFS, MDPI, vol. 9(4), pages 1-22, November.

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    More about this item

    Keywords

    procyclicality; business cycle; financial stability; PiT rating system; long run probability default;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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