LEADER 06925oam 22016574 450 001 9910817596403321 005 20200520144314.0 010 $a1-4623-3062-2 010 $a1-4527-6224-4 010 $a1-283-51662-4 010 $a9786613829078 010 $a1-4519-0996-9 035 $a(CKB)3360000000443833 035 $a(EBL)3012542 035 $a(SSID)ssj0000948582 035 $a(PQKBManifestationID)11484547 035 $a(PQKBTitleCode)TC0000948582 035 $a(PQKBWorkID)10950156 035 $a(PQKB)10727647 035 $a(OCoLC)535146946 035 $a(MiAaPQ)EBC3012542 035 $a(IMF)WPIEE2006283 035 $a(IMF)WPIEA2006283 035 $a(EXLCZ)993360000000443833 100 $a20020129d2006 uf 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPortfolio Credit Risk and Macroeconomic Shocks : $eApplications to Stress Testing Under Data-Restricted Environments /$fMiguel Segoviano 205 $a1st ed. 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2006. 215 $a1 online resource (52 p.) 225 1 $aIMF Working Papers 300 $a"December 2006." 311 $a1-4518-6543-0 320 $aIncludes bibliographical references (p. 45-50). 327 $a""Contents""; ""I. INTRODUCTION""; ""II. PORTFOLIO CREDIT RISK""; ""III. PROPOSAL TO IMPROVE PORTFOLIO CREDIT RISK MEASUREMENT""; ""IV. PROPOSED PROCEDURE FOR STRESS TESTING""; ""V. STRESS TESTING: EMPIRICAL IMPLEMENTATION IN DENMARK""; ""VI. ANALYSIS OF STRESS TESTING RESULTS""; ""VII. CONCLUSIONS""; ""Appendix 1: Entropy in a Nutshell""; ""References"" 330 3 $aPortfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on credit risk. Aiming to improve the measurement of portfolio credit risk, we propose the joint implementation of two new methodologies, namely the conditional probability of default (CoPoD) methodology and the consistent information multivariate density optimizing (CIMDO) methodology. CoPoD incorporates the effects of macroeconomic shocks into credit risk, recovering robust estimators when only short time series of loans exist. CIMDO recovers portfolio multivariate distributions (on which portfolio credit risk measurement relies) with improved specifications, when only partial information about borrowers is available. Implementation is straightforward and can be very useful in stress testing exercises (STEs), as illustrated by the STE carried out within the Danish Financial Sector Assessment Program. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2006/283 606 $aRisk 606 $aBank investments 606 $aBank loans 606 $aBank capital 606 $aAsset and liability management$2imf 606 $aAsset valuation$2imf 606 $aAsset-liability management$2imf 606 $aBanking$2imf 606 $aBanks and Banking$2imf 606 $aBanks and banking$2imf 606 $aBanks$2imf 606 $aBusiness Fluctuations$2imf 606 $aCapital and Ownership Structure$2imf 606 $aCredit risk$2imf 606 $aCredit$2imf 606 $aCycles$2imf 606 $aDepository Institutions$2imf 606 $aDynamic Analysis$2imf 606 $aEconometric and Statistical Methods: Other$2imf 606 $aFinance$2imf 606 $aFinance: General$2imf 606 $aFinancial Institutions and Services: Government Policy and Regulation$2imf 606 $aFinancial institutions$2imf 606 $aFinancial regulation and supervision$2imf 606 $aFinancial Risk and Risk Management$2imf 606 $aFinancial Risk Management$2imf 606 $aFinancial risk management$2imf 606 $aFinancial sector policy and analysis$2imf 606 $aFinancial services law & regulation$2imf 606 $aFinancing Policy$2imf 606 $aGoodwill$2imf 606 $aIndustries: Financial Services$2imf 606 $aInternational Financial Markets$2imf 606 $aLoans$2imf 606 $aMathematical Methods$2imf 606 $aMicro Finance Institutions$2imf 606 $aModel Evaluation and Selection$2imf 606 $aMonetary economics$2imf 606 $aMonetary Policy, Central Banking, and the Supply of Money and Credit: General$2imf 606 $aMoney and Monetary Policy$2imf 606 $aMoney$2imf 606 $aMortgages$2imf 606 $aOptimization Techniques$2imf 606 $aProgramming Models$2imf 606 $aStress testing$2imf 606 $aValue of Firms$2imf 607 $aDenmark$2imf 615 0$aRisk. 615 0$aBank investments. 615 0$aBank loans. 615 0$aBank capital. 615 7$aAsset and liability management 615 7$aAsset valuation 615 7$aAsset-liability management 615 7$aBanking 615 7$aBanks and Banking 615 7$aBanks and banking 615 7$aBanks 615 7$aBusiness Fluctuations 615 7$aCapital and Ownership Structure 615 7$aCredit risk 615 7$aCredit 615 7$aCycles 615 7$aDepository Institutions 615 7$aDynamic Analysis 615 7$aEconometric and Statistical Methods: Other 615 7$aFinance 615 7$aFinance: General 615 7$aFinancial Institutions and Services: Government Policy and Regulation 615 7$aFinancial institutions 615 7$aFinancial regulation and supervision 615 7$aFinancial Risk and Risk Management 615 7$aFinancial Risk Management 615 7$aFinancial risk management 615 7$aFinancial sector policy and analysis 615 7$aFinancial services law & regulation 615 7$aFinancing Policy 615 7$aGoodwill 615 7$aIndustries: Financial Services 615 7$aInternational Financial Markets 615 7$aLoans 615 7$aMathematical Methods 615 7$aMicro Finance Institutions 615 7$aModel Evaluation and Selection 615 7$aMonetary economics 615 7$aMonetary Policy, Central Banking, and the Supply of Money and Credit: General 615 7$aMoney and Monetary Policy 615 7$aMoney 615 7$aMortgages 615 7$aOptimization Techniques 615 7$aProgramming Models 615 7$aStress testing 615 7$aValue of Firms 700 $aSegoviano$b Miguel$01607298 712 02$aInternational Monetary Fund.$bMonetary and Capital Markets Dept. 801 0$bDcWaIMF 906 $aBOOK 912 $a9910817596403321 996 $aPortfolio Credit Risk and Macroeconomic Shocks$94244791 997 $aUNINA