05965oam 22012974 450 991078841480332120230828232658.01-4623-6191-91-4527-6528-61-283-51160-61-4519-0915-29786613824059(CKB)3360000000443399(EBL)3014554(SSID)ssj0000943056(PQKBManifestationID)11492236(PQKBTitleCode)TC0000943056(PQKBWorkID)10975471(PQKB)10208021(OCoLC)694141268(MiAaPQ)EBC3014554(IMF)WPIEE2006134(EXLCZ)99336000000044339920020129d2006 uf 0engur|n|---|||||txtccrReview and Implementation of Credit Risk Models of the Financial Sector Assessment Program (FSAP) /Kexue Liu, Jean Salvati, Renzo Avesani, Alin MiresteanWashington, D.C. :International Monetary Fund,2006.1 online resource (35 p.)IMF Working Papers"May 2006."1-4518-6394-2 Includes bibliographical references.""Contents""; ""I. INTRODUCTION""; ""II. THE BASIC MODEL SETTING""; ""III. MODEL 1: A SIMPLE MODEL WITH NON-RANDOM DEFAULT PROBABILITIES""; ""IV. INTRODUCING THE POISSON APPROXIMATION""; ""V. MODEL 2: THE MODEL WITH KNOWN PROBABILITIES REVISITED""; ""VI. MODEL 3: THE MODEL WITH RANDOM DEFAULT PROBABILITIES""; ""VII. THE LATENT FACTORS ASSUMPTION""; ""VIII. MODEL 4: EXTENSION OF CREDIT RISK+ WITH CORRELATED FACTORS""; ""IX. MODEL SUMMARY""; ""X. NUMERICAL IMPLEMENTATION""; ""XI. NUMERICAL EXAMPLES USING THE CREDIT RISK TOOLBOX""; ""XII. CONCLUSION""""PROBABILITY AND MOMENT GENERATING FUNCTIONS""""References""The paper presents the basic Credit Risk+ model, and proposes some modifications. This model could be useful in the stress-testing financial sector assessments process as a benchmark for credit risk evaluations. First, we present the setting and basic definitions common to all the model specifications used in this paper. Then, we proceed from the simplest model based on Bernoulli-distributed default events and known default probabilities to the fully-fledged Credit Risk+ implementation. The latter is based on the Poisson approximation and uncertain default probabilities determined by mutually independent risk factors. As an extension we present a Credit Risk+ specification with correlated risk factors as in Giese (2003). Finally, we illustrate the characteristics and the results obtained from the different models using a specific portfolio of obligors.IMF Working Papers; Working Paper ;No. 2006/134CreditManagementMathematical modelsFinancial services industryState supervisionBanks and BankingimfEconometricsimfMoney and Monetary PolicyimfPortfolio ChoiceimfInvestment DecisionsimfFinancial Institutions and Services: GeneralimfBanksimfDepository InstitutionsimfMicro Finance InstitutionsimfMortgagesimfMathematical Methods and Programming: GeneralimfComputational TechniquesimfMonetary Policy, Central Banking, and the Supply of Money and Credit: GeneralimfTime-Series ModelsimfDynamic Quantile RegressionsimfDynamic Treatment Effect ModelsimfDiffusion ProcessesimfFinancing PolicyimfFinancial Risk and Risk ManagementimfCapital and Ownership StructureimfValue of FirmsimfGoodwillimfMonetary economicsimfEconometrics & economic statisticsimfFinancial services law & regulationimfCreditimfVector autoregressionimfCredit riskimfFinancial risk managementimfCreditManagementMathematical models.Financial services industryState supervision.Banks and BankingEconometricsMoney and Monetary PolicyPortfolio ChoiceInvestment DecisionsFinancial Institutions and Services: GeneralBanksDepository InstitutionsMicro Finance InstitutionsMortgagesMathematical Methods and Programming: GeneralComputational TechniquesMonetary Policy, Central Banking, and the Supply of Money and Credit: GeneralTime-Series ModelsDynamic Quantile RegressionsDynamic Treatment Effect ModelsDiffusion ProcessesFinancing PolicyFinancial Risk and Risk ManagementCapital and Ownership StructureValue of FirmsGoodwillMonetary economicsEconometrics & economic statisticsFinancial services law & regulationCreditVector autoregressionCredit riskFinancial risk managementLiu Kexue1546585Salvati Jean1546586Avesani Renzo1546587Mirestean Alin1472716DcWaIMFBOOK9910788414803321Review and Implementation of Credit Risk Models of the Financial Sector Assessment Program (FSAP)3802284UNINA