Non – parametric estimation of conditional and unconditional loan portfolio loss distributions with public credit registry data
AbstractEmploying 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 InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 9798.
Date of creation: Sep 2006
Date of revision: Jun 2007
Credit Risk; Unconditional loss distribution; Bootstrapping;
Find related papers by JEL classification:
- G2 - Financial Economics - - Financial Institutions and Services
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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- 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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