FRM二级基础班培训讲义：信用风险测量与管理（打印版）.docx

PCreditRiskMeasurementand卜Management,83.i3.：2-203乌业®llQTopicWeightingsinFRMPartIISessionNO.Contents%Session1MarketRiskMeasurementandManagement20Session2CreditRiskMeasurementandManagement20Session3OperationalRiskandResiliency20Session4LiquidityandTreasuryRiskMeasurementandManagement15Session5RiskManagementandInvestmentManagement15Session6CurrentIssuesinFinancialMarket10FrameworkIntroductionofCreditRiskCreditDecisionandCreditAnalystKeyCreditRiskIndicatorsCreditRiskMeasurementProbabilityofDefaultCreditExposuresCounterpartyRiskCapitalStructureinBanksCreditRiskManagementMitigationofCounterpartyRiskCreditDerivativesSecuritizationRetailBankingRiskManagement4-203MSV!>.IntroductionofCreditRiskTopic1:CreditDecisionandCreditAnalyst1.CreditDecision5-2032.CreditAnalystM亚OK“CreditDecisionCreditRiskThedefaultofacounterpartyonafundamentalfinancialobligation.Anincreasedprobabilityofdefault.AhigherthanexpectedlossseverityarisingfromeitheralowerthanexpectedrecoveryorahigherthanexpectedexposureatthetimeofdefaultThedefaultofacounterpartywithrespecttothepaymentoffundsforgoodsorservicesthathavealreadybeenadvanced(settlementrisk).FourPrimaryComponentsofCreditRiskEvaluationTheobligorrscapacityandwillingnesstoRepay.Theexternalconditions.Theattributesofobligationfromwhichcreditriskarises.Thecreditriskmitigants.尊曲®*tsCreditDecisionCreditAnalysisTechniquesQualitativeCreditAnalysisTechniques-WillingnesstoRepayCharacterandreputationofaprospectiveborrower.Creditrecordofaprospectiveborrower.QuantitativeCreditAnalysisTechniques-AbilitytoRepayEvaluatingthecapabilityofanentitytoperformitsfinancialobligationsthroughacloseexaminationofnumericaldataderivedfromitsmostrecentandpastfinancialstatementsforms.7-203M业倒舞IMCreditDecisionCategoriesofCreditAnalysisFormostindividuals,factorssuchasaperson'snetworth,salary,assets,reputation,andcreditscoreareusedasfundamentalcriteria.Fornonfinancialfirms,liquidity,cashflowtogetherwithearningscapacityandprofitability,capitalposition(solvency),stateoftheeconomy,andstrengthoftheindustryareused.Forfinancialfirms,bank-specificmeasuressuchascapitaladequacy,assetquality,andthebank'sabilitytowithstandfinancialstressmustbeconsidered.Theimportanceofassetquality.Theomissionofcashflowasakeyindicator.BankInsolvencyvs.BankFailureInsolventbankscankeepgoingonandonsolongastheyhaveasourceofliquidity.8-203MW6NfiIMExercise1HBrentGulickracreditanalystwithHomeTownBankrisconsideringtheloanapplicationofasmall,localcardealership.ThedealershiphasbeensolelyownedbyBobJusticeformorethan20yearsandsellsthreebrandsofAmericanautomobiles.Becauseoftherurallocation,mostofthecarssoldinthepastbythedealershiphavebeenlargepick-uptrucksandsportsutilityvehicles.However,saleshavedeclined,andgasolinepriceshavecontinuedtoincrease.Asaresult,Justiceisconsideringsellingalineofhybridcars.JusticehasborrowedfromHomeTownBankbeforebutcurrentlydoesnothaveabalanceoutstandingwiththebank.WhichofthefollowingstatementsisnotoneofthefourcomponentsofcreditanalysisGulickshouldbeevaluatingwhenperformingthecreditanalysisforthispotentialloan?Exercise1A.Thebusinessenvironment,competition,andeconomicclimateintheregion.B.Justice'scharacterandpastpaymenthistorywiththebank.C.Thecardealership'sbalancesheetsandincomestatementsforthelastfewyearsaswellasJustice'spersonalfinancialsituation.D.ThefinancialhealthofJustice'sfriendsandfamilywhocouldbecalledupontoguaranteetheloan.10-203Answer:DMWMfi!Exercise2RichardMarshallFRM,isaratingagencyanalystwhoiscurrentlyperformingfinancialstatementanalysisonam¾orbank.Whichofthefollowingfinancialstatementswouldbeleastusefulforbankcreditanalysis?A.Balancesheet.B.Incomestatement.C.Statementofcashflows.D.Statementofchangesincapitalfunds.11-203Answer:CMW/em!«CreditAnalystCreditAnalysis:ToolsandMethodsQuantitativeElementsInvolvesthecomparisonoffinancialindicatorsandratios.Moreamenabletostatisticaltechniquesandautomation.NominallyobjectiveQualitativeElementsConcernsthoseattributesthataffecttheprobabilityofdefault,butwhichcannotbedirectlyreducedtonumbers.Consequently,theevaluationofsuchattributesmustbeprimarilyamatterofjudgment.Reliesheavilyonanalystsperceptions,experiencejudgment,reasoning,andintuition.Nominallysubjective.CreditAnalysis:ToolsandMethodsResearchSkillsPrimaryresearchskillsincludedetailedanalysisofauditedfinancialstatementsforseveralyearstogetherwithannualreportsandrecentinterimfinancialstatements.Secondaryresearchskillsinvolveusingtheresearchpublishedbyothers(e.g.4ratingagencies).SourcesofInformationusedbyCreditAnalystAnnualreports;Interimfinancialstatements;Financialdatasources;Newsservices;Ratingagencyreportsandotherthird-partyresearch;Prospectusesandregulatoryfillings;Notesfromthebankvisitandthirdparties;Auditor'sreportorstatement;Auditorsopinion;Thebankwebsite;News,theInternetandsecuritiespricingdataMwrelei“CreditAnalystCAMELSystemBankcreditanalystsuniversallyemploytheCAMELsystemtoevaluatebankcreditrisk.Itcanbeseenasachecklistoftheattributesofabankthatareviewedascriticalinevaluatingitsfinancialperformance.FiveMostImportantAttributesofBankFinancialHealthC:CapitalA:AssetQualityM:ManagementE:Earnings1.Liquidity14-203Amenabletoratioanalysisswam*IntroductionofCreditRiskTopic2:KeyCreditRiskIndicators1.CreditRiskIdentification2.ThreeDrivers3.KeyIndicators4.CapitalStructure1S-2O3CreditRiskIdentificationCredit Risk of Different Financial ProductsLending RiskCounterparty Risk: risk to each party of a contract that the counterparty will not live up to its contractual obligations.ForwardSWaPOptionExotic OptionThree DriversProbability of Default (PD)Exposure at Default (EAD)Loss given Default (LGD)Key IndicatorsExpected Loss and Unexpected Loss (Credit VaR) Three DriversProbability of Default (PD)Likelihood that a borrower will default within a specified time horizon.Credit migrations or discrete changes in credit quality (such as those due to ratings changes) are crucial, since they influence the term structure of default probability.Exposure at Default (EAD)Amount of money lender can lose in the event of a borrower default.Loss given Default (LGD)The amount of creditor loss in the event of a defaultFraction of exposure recovered at default is recovery.recovery LGDRR =I-exposureexposure Key IndicatorsExpected Loss (EL)Expected value of credit Iossr and represents the portion of loss a creditor should provision for. If the only possible credit event is default, expected loss is equal to:EL=PDXa- RR) X EAD = PDX LGD X EADUnexpected Loss (Credit VaR)Is typically defined in terms of unexpected loss (UL) as the worst-case portfolio loss at a given confidence level over a specific holding period, minus the expected loss.UL = Credit VaR = WCL - ELKeyIndicatorsCreditVaRversusMarketVaRExtremeskewnessisamaterialconcernincreditrisk.Extremeskewnessarisesgiven,intherareeventthatdefaultdoesoccur,returnsareverylargeandnegative.SkewnessresultsinahigherconfidenceintervalformeasuringcreditVaRfusuallyat99thand99.9thpercentiles.Thetimehorizonsformarketriskarealmostalwaysbetweenonedayandonemonth.ButthetypicaltimehorizonformeasuringcreditriskismuchIOngeLoften,thecreditriskhorizonisoneyear.TyPeMarketRiskCreditRiskDistributionsSymmetricFattailsSkewedtotheleftTimeHorizonShortTerm(Days)LongTerm(Years)19-203M业倒舞IMKeyIndicators1.ossDistributionMW6NfiIMKeyIndicatorsExampleCaseStudy1:Oneloanwithprincipalof!million,PD=8%,RR=40%.Howmuchshouldbankprovisionfor?CaseStudy2:Consideraportfolioof$100millionwith3bondsA,B.andCwithvariousprobabilitiesofdefault.Theexposuresareconstant.Therecoveryincaseofdefaultiszero.Defaulteventsareindependentacrossissuers.Thefollowingsdisplaytheexposuresanddefaultprobabilities.!issuerExposureProbabilityIA$250.05B$300,1C$4502KeyIndicators22-203ExampleIDefaultLossLiProbabilityP(Li)CumulativeProb.ExpectedLp(L)Variance(Li-Eli)2P(Li)None$00.6840.684$0.00120.08A$250.0360.720$0.9。4.97B$300.07607%$2.282132C$450.171S967$7.7017238A,B$550.0040.971$0.226.97AfCB.C$70$750.0090.0190.9800.999$0.63$14328.9972.45ARC$1000.001LooO$0.10$13.257.53434.69M亚mIMKeyIndicatorsExampleTheexpectedcreditlossoftheportfoliois:E(CL)=pj×CEi=0.05×25+0.10×30+0.20×45=13.25L=WCL-EL=45m-13.25m=31.75mDistributionofCreditLosses0.60.70.60.50.40.30.20.10T(X)=75"70=553530由501.ossKeyIndicatorsPortfolioCreditVaRDefaultCorrelationEstimationDefaultCorrelationdrivesthelikelihoodofhavingmultipledefaultsinacreditportfolio.SimplestFrameworkTwofirms(orcountries,ifwehavepositionsinsovereigndebt).Withprobabilitiesofdefault11f=and2Oversometimehorizon=Andajointdefaultprobability-theprobabilitythatbothdefaultover-equalton豆.KeyIndicatorsPortfolioCreditVaRDefaultCorrelationEstimationOutcomeXiX之XX2ProbabilityNodefault00o11-T一+五Firm1onlydefaults10CFirm2onlydefaults01CBothfirmsdefault111久整E(Xi)=i;E(X1X2)=K12E42V(XgE闾)-E(W-1(1FiROP=VlrWlCov(X1,X2)=E(X1X2)-E(X1)E(X2)=12-12KeyIndicatorsPortfolioCreditVaREstimationofPortfolioCreditVaRDefaultcorrelationaffectstheextremequantilesoflossorworstcaselossratherthantheexpectedloss.Ifdefaultcorrelationinaportfolioofcreditsisequalto1,thentheportfoliobehavesasifitconsistedofjustonecredit.Nocreditdiversificationisachieved.26-203Ifdefaultcorrelationisequalto0,thenthenumberofdefaultsintheportfolioisabinomiallydistributedrandomvariable.Significantcreditdiversificationmaybeachieved.swam*11KeyIndicatorsPortfolioCreditVaREstimationofPortfolioCreditVaR(con't)p=l(theportfoliowillactasifthereisonlyonecredit)Givenaportfoliowithnotionalvalueof$1,000,000and20creditpositions.EachcreditshasaPDof2%andaRRof0.Eachcreditpositionisanobligationfromthesameobligorsothatthecreditportfoliohasadefaultcorrelationequalto1.Whatisthecreditvalueatriskatthe99%confidencelevelforthisportfolio?EL=1,000,000×2%=20,000WCL(99%)=1,(KX)zOOOCreditVaR=l,000,000-20,000=980,000PortfolioCreditVaREstimationofPortfolioCreditVaR=0(numberofdefaultsisbinomiallydistributed)Givenaportfoliowithavalueof$1,000,000and50credits.Eachcreditisequallyweightedandhasaterminalvalueof$20,000eachifnodefaultoccurs.EachcreditshasaPDofandaRRofzero.Whatisthecredit=VaRat95%confidencelevelifis2%andthedefaultcorrelationis0?=(the95thpercentileofthenumberofdefaultsbasedonthisdistributionis3)?EL=1,000,000×2%=20,000WCL(95%)=3×20,000=60,000CreditVaR=60x000-20,000=40,000KeyIndicatorsEffectofGranularityonCreditVaRWhentheportfoliobecomesmoregranular,thatis,containsmoreindependentcredits,eachofwhichisasmallerfractionoftheportfolio.TheCreditVaRis.naturally,higherforahigherprobabilityofdefault,giventheportfoliosize.Butitdecreasesasthecreditportfoliobecomesmoregranularforagivendefaultprobability.Butthathasanimportantconverse:ItishardertoreduceVaRbymakingtheportfoliomoregranular,ifthedefaultprobabilityislow.Eventually,foracreditportfoliocontainingaverylargenumberofindependentsmallpositions,theprobabilityconvergesto100percentthatthecreditlosswillequaltheexpectedloss.Theportfoliothenhaszerovolatilityofcreditloss,andtheCreditVaRiszero.CapitalStructureStepstoDeriveEconomicCapitalforCreditRiskExpectedLosses(EL)UnexpectedLosses(UL-StandaIone)UnexpectedLossContribution(ULC)EconomicCapitalELandUL(instatisticalterms)EL三PDxEAxLRUL=EA×Jpd×112r+LR2×WhereOLR=standarddeviationofthelossrateLRD=standarddeviationofthedefaultprobabilityPD2=PD×(1-PD)CapitalStructureExampleSupposeXYZbankhasbookedaloanwiththefollowingcharacteristics:totalcommitmentof$2,000,000,ofwhich$1,200,000iscurrentlyoutstanding.Thebankhasassessedaninternalcreditratingequivalenttoa1%defaultprobabilityoverthenextyear.Drawdownupondefaultisassumedtobe75%.Thebankhasadditionallyestimateda40%lossgivendefault.ThestandarddeviationofEDFandLGDis5%and30%,respectively.CalculatetheunexpectedlossforXYZbank.EA=1,200,000+800,000×75%=lf800,000UL=1,800,000×1%×30%2+40%2×5%2=64,900CapitalStructureUnexpectedLossContributionOULP1ULMCi=xJPOULi2ULpULj1/(nPULUL)_£y=JU02ULp"h1Cd!,，LUvTotalContributiontothePortfoliosULnULP=>ULMCiXULii=ELUkULCi=ULMCl×UL1=11×ULi32-203SWrel»!i31-203Mwrelei“CapitalStructureEconomicCapitalAsdefinedpreviously,theamountofeconomiccapitalneededisthedistancebetweentheexpectedoutcomeandtheunexpectedoutcomeatacertainconfidencelevel.Unexpectedlossistranslatedintoeconomiccapitalforcreditriskinthreesteps:First,thestandaloneunexpectedlossiscalculated.Then,thecontributionofthestandaloneULtotheULofthebankportfolioisdetermined.Finally,thisunexpectedlosscontribution(ULC)istranslatedintoeconomiccapital.CapitalStructureEconomic CapitalEconomicCapitalp=ULp×CMEConomiCC叩ital=ULC×CM1ICM=capitalmultiplier与业色iIVCapitalStructureChallengestoQuantifyingCreditRiskThisapproachassumesthatcreditsareilliquidassets.Sincethecreditriskofbankloansbecomesmoreandmoreliquidandistradedinthecapitalmarkets,avalueapproachwouldbemoresuitable.35-203Thiswouldrequiremodelingthemulti-periodnatureofcreditsand,hence,theexpectedandunexpectedchangesinthecreditqualityoftheborrowers(andtheircorrelations).Themoreprecisenumericalsolutionsgetverycomplexandcumbersome.Therefore,almostallinternalcreditriskmodelsusedinpracticeuseonlyaone-yearestimationhorizon.Althoughthisapproachconsiderscorrelationsatapracticablelevelwithinthesamerisktype,itassumes,whenmeasuring,thatallotherriskcomponents(suchasmarketandoperationalrisk)areseparatedandaremeasuredandmanagedindifferentdepartmentswithinthebank.MW/em“Exercise1SupposeBankZlendsEUR1milliontoXandEUR5milliontoY.Overthenextyear,thePDforXis0.2andforYis03.ThePDofjointdefaultis0.1.Thelossgivendefaultis40%forXand60%forY.Whatistheexpectedlossofdefaultinoneyearforthebank?A.EUR0.72millionB.EUR0.98millionC.EUR0.46millionD.EUR0.64millionAnswer:BCreditRiskMeasurement1. Z3.4.6.Topic 1: Probability of DefaultBasic Approaches used to Predicting DefaultRating SystemMeasurement from Market PricesExponential DistributionSingle Factor ModelOther Models37-203Mwrelei “BasicApproachesusedtoPredictingDefaultExperts-Based,Statistical-basedandNumericalApproachesExperts-BasedStatistical-BasedHeuristicandNumericalApproachStructuralApproachesandReduced-FormApproachesStru