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Non – parametric estimation of conditional and unconditional loan portfolio loss distributions with public credit registry data

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  • Gutierrez Girault, Matias

Abstract

Employing a resampling-based Monte Carlo simulation developed in Carey (2000, 1998) and Majnoni, Miller and Powell (2004), in this paper we estimate conditional and unconditional loss distributions for loan portfolios of argentine banks in the period 1999-2004, controlling by type of borrower and type of bank. The exercise, performed with data contained in the public credit registry of the Central Bank of Argentina, yields economic estimates of expected and unexpected losses useful in bank supervision and in the prudential regulation of credit risk, for example to measure if Basel II’s IRB approach is appropriately calibrated to the local economy.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 9798.

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Date of creation: Sep 2006
Date of revision: Jun 2007
Handle: RePEc:pra:mprapa:9798

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Related research

Keywords: Credit Risk; Unconditional loss distribution; Bootstrapping;

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References

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  1. Mark Carey, 2000. "Dimensions of credit risk and their relationship to economic capital requirements," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2000-18, Board of Governors of the Federal Reserve System (U.S.).
  2. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, Elsevier, vol. 12(3), pages 199-232, July.
  3. Mark Carey, 1998. "Credit Risk in Private Debt Portfolios," Journal of Finance, American Finance Association, American Finance Association, vol. 53(4), pages 1363-1387, 08.
  4. Mark Carey, 2000. "Dimensions of Credit Risk and Their Relationship to Economic Capital Requirements," NBER Working Papers 7629, National Bureau of Economic Research, Inc.
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Cited by:
  1. Rodriguez, Analía, 2007. "Distribución de pérdidas de la cartera de créditos: el método unifactorial de Basilea II vs. estimaciones no paramétricas," MPRA Paper 12637, University Library of Munich, Germany.
  2. Gutierrez Girault, Matias Alfredo, 2008. "Modeling extreme but plausible losses for credit risk: a stress testing framework for the Argentine Financial System," MPRA Paper 16378, University Library of Munich, Germany.
  3. Rodríguez Dupuy, Analía, 2007. "Loan portfolio loss distribution: Basel II unifactorial approach vs. Non parametric estimations," MPRA Paper 10697, University Library of Munich, Germany.
  4. Girault, Matias Gutierrez & Hwang, Jane, 2010. "Public credit registries as a tool for bank regulation and supervision," Policy Research Working Paper Series 5489, The World Bank.

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