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dc.creatorCabrera-Rodríguez, Wilmar Alexander
dc.creatorGutiérrez-Rueda, Javier
dc.creatorMendoza-Gutiérrez, Juan Carlos
dc.date.created2012-09-01
dc.date.issued2012-09
dc.identifier.urihttps://repositorio.banrep.gov.co/handle/20.500.12134/2135
dc.description.abstractIn this paper we seek to assess the ability of banks to withstand the effects of an increase in credit risk as a result of changes in the macroeconomic environment. To do so we estimate a credit risk model for each loan type as a function of four macroeconomic variables commonly used in the literature. Then, we forecast the dynamics of non-performing loans (NPL) and total loans in a stressed scenario in a time span of 8 quarters. Using these results, we quantify the effects of the macroeconomic shock on bank’s performance indicators, such as the NPL ratio, the return on assets, and the capital adequacy ratio. The results suggest that most Colombian banks are able to withstand a large shock to economic activity. We also perform a reverse stress testing to quantify how much NPL should increase in order to bring the earnings before taxes to zero.
dc.format.extent20 páginas : ilustraciones, gráficas, tablas
dc.format.mimetypePDF
dc.language.isoeng
dc.publisherBanco de la República de Colombia
dc.relation.ispartofDocumentos de Trabajo
dc.relation.ispartofseriesTemas de Estabilidad Financiera
dc.relation.isversionofTemas de Estabilidad Financiera ; No. 73
dc.rights.accessRightsOpen Access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectPruebas de estrés
dc.subjectCréditos en mora
dc.subjectRetorno de activos
dc.subjectCoeficiente de solvencia
dc.titleCredit risk stress testing : an exercise for colombian banks
dc.typeWorking Paper
dc.subject.jelC25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
dc.subject.jelD22 - Firm Behavior: Empirical Analysis
dc.subject.jelG21 - Banks; Depository Institutions; Micro Finance Institutions; Mortgages
dc.subject.jelG33 - Bankruptcy; Liquidation
dc.audiencePolicymakers
dc.audienceResearchers
dc.audienceStudents
dc.audienceTeachers
dc.subject.keywordVECX
dc.subject.keywordStress testing
dc.subject.keywordNon-performing loans
dc.subject.keywordReturn on assets
dc.subject.keywordCapital adequacy ratio
dc.subject.lembRiesgo bancario -- Colombia
dc.subject.lembPréstamos bancarios -- Colombia
dc.subject.lembRiesgo crediticio -- Colombia
dc.type.spaDocumentos de trabajo
dc.rights.spaAcceso abierto
dc.rights.ccAtribucion-NoComercial-CompartirIgual CC BY-NC-SA 4.0
dc.subject.jelspaC25 - Modelos de regresión discreta y elección cuantitativa; Regresores discretos; Proporciones; Probabilidad
dc.subject.jelspaD22 - Comportamiento de la empresa: análisis empíricos
dc.subject.jelspaG21 - Bancos; Instituciones de depósito; Instituciones Microfinancieras; Hipotecas
dc.subject.jelspaG33 - Insolvencia; Liquidación
dc.type.hasversionPublished Version
dc.coverage.sucursalBogotá
dc.source.bibliographicCitationBreusch, T. (1978), ‘Testing for Autocorrelation in Dynamic Linear Models’, Australien Economic Papers (17), 334–355.
dc.source.bibliographicCitationEdgerton, D. & Shukur, G. (1999), ‘Testing Autocorrelation in a System Perspective’, Econometric Reviews (18), 343–386.
dc.source.bibliographicCitationWong, J., Choi, K. & Fong, T. (2008), ‘A Framework for Stress Testing Banks’ Credit Risk’, The Journal of Risk Model Validation 2(1), 3–23.
dc.relation.doihttps://doi.org/10.32468/tef.73
dc.rights.disclaimerLas opiniones contenidas en el presente documento son responsabilidad exclusiva de los autores y no comprometen al Banco de la República ni a su Junta Directiva.
dc.relation.repechttps://ideas.repec.org/p/bdr/temest/073.html
dc.identifier.handlehttps://hdl.handle.net/20.500.12134/2135
dc.source.handleRepecRePEc:bdr:temest:073


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