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Ratings based Inference and Credit Risk: Detecting likely-to-fail Banks with the PC-Mahalanobis Method

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  • Pompella, Maurizio
  • Dicanio, Antonio

Abstract

This paper proposes a new approach of how to test the validity of bank ratings assigned by Rating Agencies. An innovative Early Warning System (EWS) is introduced that allows to unveil prodromic signals of instability for selected individual banks, and possibly forecast bank failures. A forward-looking, credit risk model that is based on financial ratios is designed to assess the financial position of rated banks. This approach allows to discriminate between banks that are in a stable, financially healthy position, and banks that are possibly going to become insolvent (likely-to-fail banks). Our empirical results are compared with the official ratings assigned by RAs to the same intermediaries. Our findings reveal incoherent positions and possibly incorrectly rated banks. We argue that our method can be easily implemented by financial regulators.

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  • Pompella, Maurizio & Dicanio, Antonio, 2017. "Ratings based Inference and Credit Risk: Detecting likely-to-fail Banks with the PC-Mahalanobis Method," Economic Modelling, Elsevier, vol. 67(C), pages 34-44.
    • Handle: RePEc:eee:ecmode:v:67:y:2017:i:c:p:34-44
    DOI: 10.1016/j.econmod.2016.08.023
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    as
    1. Castro, Vítor, 2013. "Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI," Economic Modelling, Elsevier, vol. 31(C), pages 672-683.
    2. Duffee, Gregory R, 1999. "Estimating the Price of Default Risk," Review of Financial Studies, Society for Financial Studies, vol. 12(1), pages 197-226.
    3. Williams, Gwion & Alsakka, Rasha & ap Gwilym, Owain, 2013. "The impact of sovereign rating actions on bank ratings in emerging markets," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 563-577.
    4. Betz, Frank & Oprică, Silviu & Peltonen, Tuomas A. & Sarlin, Peter, 2014. "Predicting distress in European banks," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 225-241.
    5. Rebel Cole & Lawrence White, 2012. "Déjà Vu All Over Again: The Causes of U.S. Commercial Bank Failures This Time Around," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 5-29, October.
    6. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    7. Periklis Gogas & Theophilos Papadimitriou & Anna Agrapetidou, 2014. "Forecasting bank credit ratings," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 15(2), pages 195-209, March.
    8. Robert A. Jarrow & David Lando & Stuart M. Turnbull, 2008. "A Markov Model for the Term Structure of Credit Risk Spreads," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 18, pages 411-453, World Scientific Publishing Co. Pte. Ltd..
    9. Patrick Roy, 2013. "Is There a Difference Between Solicited and Unsolicited Bank Ratings and, If So, Why?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 44(1), pages 53-86, August.
    10. Öğüt, Hulisi & Doğanay, M. Mete & Ceylan, Nildağ Başak & Aktaş, Ramazan, 2012. "Prediction of bank financial strength ratings: The case of Turkey," Economic Modelling, Elsevier, vol. 29(3), pages 632-640.
    11. 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.
    12. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, vol. 54(4), pages 361-387.
    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. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    15. Sahut, Jean-Michel & Mili, Mehdi, 2011. "Banking distress in MENA countries and the role of mergers as a strategic policy to resolve distress," Economic Modelling, Elsevier, vol. 28(1), pages 138-146.
    16. Qin, Xiao & Luo, Chengying, 2014. "Capital account openness and early warning system for banking crises in G20 countries," Economic Modelling, Elsevier, vol. 39(C), pages 190-194.
    17. Hulisi Ögüt & M. Mete Doganay & Nildag Basak Ceylan & Ramazan Aktas, 2012. "Predicting Bank Financial Strength Ratings in an Emerging Economy: The Case of Turkey," Working Papers 740, Economic Research Forum, revised 2012.
    18. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
    19. Alessandro Santoni & Barbara Arbia, 2013. "Assessing Rating Agencies' Ability to Predict Bank Bankruptcy – The Lace Financial Case," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(2), pages 203-215, July.
    20. Jin, Justin Yiqiang & Kanagaretnam, Kiridaran & Lobo, Gerald J. & Mathieu, Robert, 2013. "Impact of FDICIA internal controls on bank risk taking," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 614-624.
    21. DeYoung, Robert & Torna, Gökhan, 2013. "Nontraditional banking activities and bank failures during the financial crisis," Journal of Financial Intermediation, Elsevier, vol. 22(3), pages 397-421.
    22. Caporale, Guglielmo Maria & Matousek, Roman & Stewart, Chris, 2012. "Ratings assignments: Lessons from international banks," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1593-1606.
    23. Lin, Ching-Chung & Yang, Shou-Lin, 2016. "Bank fundamentals, economic conditions, and bank failures in East Asian countries," Economic Modelling, Elsevier, vol. 52(PB), pages 960-966.
    24. Kato, Ryo & Tsuruga, Takayuki, 2016. "The safer, the riskier: A model of financial instability and bank leverage," Economic Modelling, Elsevier, vol. 52(PA), pages 71-77.
    25. Periklis Gogas & Theophilos Papadimitriou & Anna Agrapetidou, 2014. "Forecasting bank credit ratings," Journal of Risk Finance, Emerald Group Publishing, vol. 15(2), pages 195-209, March.
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    3. Alexander M. Karminsky & Ella Khromova, 2018. "Increase of banks’ credit risks forecasting power by the usage of the set of alternative models," Russian Journal of Economics, ARPHA Platform, vol. 4(2), pages 155-174, June.
    4. Aggarwal, Nidhi & Singh, Manish K. & Thomas, Susan, 2023. "Do decreases in Distance-to-Default predict rating downgrades?," Economic Modelling, Elsevier, vol. 129(C).

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