FRM二級(jí)基礎(chǔ)班培訓(xùn)課件：信用風(fēng)險(xiǎn)測(cè)量與管理

FRM二級(jí)培訓(xùn)講義-基礎(chǔ)班CreditRiskMeasurement

andManagementTopicWeightingsinFRMPart

II3-203Session

NO.Contents%Session1MarketRiskMeasurementand

Management20Session2CreditRiskMeasurementand

Management20Session3OperationalRiskand

Resiliency20Session4LiquidityandTreasuryRiskMeasurementandManagement15Session5RiskManagementandInvestment

Management15Session6CurrentIssuesinFinancial

Market10FrameworkIntroductionofCredit

RiskCreditDecisionandCredit

AnalystKeyCreditRisk

IndicatorsCreditRisk

MeasurementProbabilityof

DefaultCredit

ExposuresCounterparty

RiskCapitalStructurein

BanksCreditRisk

ManagementMitigationofCounterparty

RiskCredit

DerivativesSecuritizationRetailBankingRisk

Management4-203Introduction

ofCredit

Risk5-203Topic1:CreditDecisionandCredit

AnalystCredit

DecisionCredit

AnalystCredit

Decision6-203Credit

RiskThe

default

of

a

counterparty

on

a

fundamental

financial

obligation.Anincreasedprobabilityof

default.Ahigherthanexpectedlossseverityarisingfromeitheralowerthanexpected

recovery

or

a

higher

than

expected

exposure

at

the

time

ofdefault.The

default

of

a

counterparty

with

respect

to

the

payment

of

funds

forgoods

or

services

that

have

already

been

advanced

(settlement

risk).FourPrimaryComponentsofCreditRisk

EvaluationTheobligor’scapacityandwillingness

to

Repay.Theexternal

conditions.Theattributesofobligationfromwhichcreditrisk

arises.Thecreditrisk

mitigants.Credit

Decision7-203CreditAnalysis

TechniquesQualitativeCreditAnalysisTechniques–Willingnessto

RepayCharacterandreputation

ofaprospective

borrower.Creditrecord

ofaprospective

borrower.QuantitativeCreditAnalysisTechniques–Abilityto

RepayEvaluatingthecapabilityofanentitytoperformitsfinancial

obligationsthroughacloseexaminationofnumerical

dataderivedfromitsmostrecentandpastfinancialstatements

forms.Credit

Decision8-203CategoriesofCredit

AnalysisFormostindividuals,factorssuchasaperson’snetworth,salary,assets,reputation,andcreditscore

areusedasfundamental

criteria.Fornonfinancialfirms,liquidity,cashflowtogetherwithearningscapacityandprofitability,capitalposition(solvency),stateoftheeconomy,andstrengthoftheindustry

are

used.Forfinancialfirms,

bank-specificmeasuressuchascapitaladequacy,assetquality,andthebank’sabilitytowithstandfinancialstressmustbeconsidered.Theimportanceofasset

quality.Theomissionofcashflowasakey

indicator.BankInsolvencyvs.Bank

FailureInsolventbankscankeepgoingonandonsolongastheyhaveasourceofliquidity.Exercise

1BrentGulick,acreditanalystwithHomeTownBank,isconsideringtheloanapplicationofasmall,localcardealership.ThedealershiphasbeensolelyownedbyBobJusticeformorethan20yearsandsellsthreebrandsofAmericanautomobiles.Becauseoftherurallocation,mostofthecarssoldinthepastbythedealershiphavebeenlargepick-uptrucksandsportsutilityvehicles.However,saleshave

declined,andgasolinepriceshavecontinuedtoincrease.Asaresult,Justiceisconsideringsellingalineofhybridcars.JusticehasborrowedfromHomeTownBankbeforebutcurrentlydoesnothaveabalanceoutstandingwiththebank.WhichofthefollowingstatementsisnotoneofthefourcomponentsofcreditanalysisGulickshouldbeevaluatingwhenperformingthecreditanalysisforthispotential

loan?9-203Exercise

1The

business

environment,

competition,

and

economic

climate

inthe

region.Justice'scharacterandpastpaymenthistory

withthebank.The

car

dealership's

balance

sheets

and

income

statements

for

thelastfewyearsaswellasJustice'spersonal

financialsituation.ThefinancialhealthofJustice'sfriendsandfamilywhocould

becalledupontoguaranteethe

loan.Answer:

D10-203Exercise

2RichardMarshall,FRM,isaratingagencyanalystwhoiscurrentlyperformingfinancialstatementanalysisonamajorbank.Whichof

thefollowingfinancialstatementswouldbeleastusefulforbankcreditanalysis?Balance

sheet.Income

statement.Statementofcash

flows.Statementofchangesincapital

funds.Answer:

C2021CFA&FRM11-203Credit

Analyst12-203CreditAnalysis:Toolsand

MethodsQuantitative

ElementsInvolvesthecomparisonoffinancialindicatorsand

ratios.Moreamenabletostatisticaltechniquesand

automation.Nominally

objectiveQualitative

ElementsConcernsthoseattributesthataffecttheprobabilityofdefault,but

whichcannotbedirectlyreducedtonumbers.Consequently,theevaluationofsuchattributesmustbeprimarilyamatterof

judgment.Relies

heavily

on

analyst’s

perceptions,

experience,

judgment,

reasoning,and

intuition.Nominally

subjective.Credit

Analyst13-203CreditAnalysis:Toolsand

MethodsResearch

SkillsPrimary

researchskills includedetailedanalysisofaudited

financialstatements

for

several

years

together

with

annual

reports

and

recent

interimfinancial

statements.Secondaryresearchskillsinvolveusingtheresearchpublished

byothers(e.g.,rating

agencies).SourcesofInformationusedbyCredit

AnalystAnnualreports;Interimfinancialstatements;Financialdatasources;Newsservices;Ratingagencyreportsandother

third-partyresearch;Prospectusesandregulatoryfillings;Notesfromthebankvisitand

thirdparties;Auditor’sreportorstatement;Auditor’sopinion;Thebankwebsite;

News,

the

Internet,

and

securities

pricing

dataCredit

Analyst14-203CAMEL

SystemBankcreditanalystsuniversallyemploytheCAMELsystemtoevaluatebankcreditrisk.Itcanbeseen

asachecklistoftheattributesofabankthatareviewedascriticalinevaluatingitsfinancial

performance.FiveMostImportantAttributesofBankFinancial

HealthC:

CapitalA:Asset

QualityM:

ManagementE:

EarningsL:

LiquidityAmenabletoratio

analysisIntroduction

ofCredit

Risk15-203Topic2:KeyCreditRisk

IndicatorsCreditRisk

IdentificationThree

DriversKey

IndicatorsCapital

StructureCreditRisk

IdentificationCreditRiskofDifferentFinancial

ProductsLoanForwardSwapOptionExotic

OptionThree

DriversProbabilityofDefault

(PD)ExposureatDefault

(EAD)LossgivenDefault

(LGD)Key

IndicatorsExpectedLossandUnexpected

Loss(CreditVaR)Lending

RiskCounterpartyRisk:risktoeachpartyofacontractthatthecounterpartywillnotliveuptoitscontractual

obligations.16-203Three

DriversProbabilityofDefault

(PD)Likelihoodthataborrowerwilldefaultwithinaspecifiedtime

horizon.Creditmigrationsordiscretechangesincreditquality(suchas

thosedue

to

ratings

changes)

are

crucial,

since

they

influence

the

termstructureofdefault

probability.ExposureatDefault

(EAD)Amount

of

money

lender

can

lose

in

the

event

of

a

borrower’s

default.LossgivenDefault

(LGD)Theamountofcreditorlossintheevent

ofadefault.Fractionofexposurerecoveredatdefaultis

recovery.RR=recovery=

1

? LGDexposure exposure17-203Key

IndicatorsExpectedLoss

(EL)Expectedvalueofcreditloss,andrepresentstheportionoflossacreditor

should

provision

for.If

the

only

possible

credit

event

is

default,expectedlossisequal

to:UnexpectedLoss(Credit

VaR)Istypicallydefinedintermsofunexpectedloss(UL)astheworst-caseportfoliolossatagivenconfidenceleveloveraspecificholding

period,minustheexpected

loss.EL=

PD

× 1

?

RR ×EAD=PD×LGD×

EAD18-203UL=CreditVaR=WCL?

ELKey

Indicators19-203CreditVaRversusMarket

VaRExtremeskewness

isamaterialconcern

increditrisk.Extremeskewnessarises

given,

in

the

rare

event

that

default

does

occur,

returns

are

verylarge

and

negative.

Skewness

results

in

a

higher

confidence

interval

for

measuringcreditVaR,usuallyat99thand99.9th

percentiles.The

time

horizons

for

market

risk

are

almost

always

between

one

dayand

one

month.

But

the

typical

time

horizon

for

measuring

creditrisk

ismuch

longer,

often,

the

credit

risk

horizon

is

one

year.TypeMarket

RiskCredit

RiskDistributionsSymmetricFat

tailsSkewedtothe

leftTime

HorizonShortTerm

(Days)LongTerm

(Years)Loss

DistributionKey

Indicators20-203Key

Indicators21-203ExampleCaseStudy1:Oneloanwithprincipalof1million,PD=8%,RR=

40%.Howmuchshouldbankprovision

for?CaseStudy2:Consideraportfolioof$100millionwith3bondsA,

B,andC,withvariousprobabilitiesof

default.Theexposuresare

constant.Therecoveryincaseofdefaultis

zero.Defaulteventsareindependentacross

issuers.Thefollowingsdisplaytheexposuresanddefault

probabilities.IssuerExposureProbabilityA$250.05B$300.1C$450.2Key

Indicators22-203ExampleDefaultiLossLiProbabilityp(Li)CumulativeProb.ExpectedLip(Li)Variance(Li-Eli)2p(Li)None$00.6840.684$0.00120.08A$250.0360.720$0.904.97B$300.0760.796$2.2821.32C$450.1710.967$7.70172.38A,B$550.0040.971$0.226.97A,C$700.0090.980$0.6328.99B,C$750.0190.999$1.4372.45A,B,C$1000.0011.000$0.107.53$13.25434.69Key

Indicators0.80.70.60.50.40.30.20.10-100-75 -70 -55 -45 -30 -25 0FrequencyLossProbabilityExpected

LossUnexpected

LossP

CL

CLi

95%Credit

VaRTheDeviationsfromthe

Mean23-203ExampleTheexpectedcreditlossoftheportfolio

is:E(CL)=∑pi×CEi=0.05×25+0.10×30+0.20×45=

13.25UL=WCL-EL=45m-13.25m=31.75mDistributionofCredit

LossesKey

Indicators24-203PortfolioCreditVaRDefaultCorrelation

EstimationDefaultCorrelationdrivesthelikelihoodofhavingmultipledefaultsinacredit

portfolio.Simplest

FrameworkTwofirms(orcountries,

ifwehavepositionsinsovereigndebt).Withprobabilitiesofdefaultπ1and

π2.Oversometimehorizon

τAndajointdefaultprobability–theprobabilitythatbothdefaultoverτ

–equalto

π12.Key

IndicatorsPortfolioCreditVaRDefaultCorrelation

EstimationOutcomeX1X2X1X2ProbabilityNo

default0001–π1–π2+

π12Firm1only

defaults100π1–

π12Firm2only

defaults010π2–

π12Bothfirms

default111π12E

Xi =πi;

E(X1X2)=π12V(Xi)=E(X2)?[E(X

)]2=π 1

?

π i=1,2i i i iCov(X1,X2)=E(X1X2)-E(X1)E(X2)=π12?

π1π2ρ

=π12?

π1π2π1

1

?

π1 π2(1?

π2)25-203Key

Indicators26-203PortfolioCreditVaREstimationofPortfolioCredit

VaRDefault

correlation

affects

the

extreme

quantiles

of

loss

or

worst

caselossratherthantheexpected

loss.Ifdefaultcorrelationinaportfolioofcreditsisequalto1,then

theportfoliobehavesasifitconsistedofjustonecredit.No

creditdiversificationis

achieved.Ifdefaultcorrelationisequalto0,thenthenumberofdefaults

intheportfolioisabinomiallydistributedrandomvariable.Significant

creditdiversificationmaybe

achieved.Key

Indicators27-203PortfolioCreditVaREstimationofPortfolioCreditVaR

(con’t)ρ=1(theportfoliowillactasifthereisonlyone

credit)Givenaportfoliowithnotionalvalueof$1,000,000and20creditpositions.EachcreditshasaPDof2%andaRRof0.Each

creditpositionisanobligationfromthesameobligorsothatthecreditportfoliohasadefaultcorrelationequalto1.Whatisthecreditvalueatriskatthe99%confidencelevelforthis

portfolio?EL=1,000,000×2%=

20,000WCL(99%)=1,000,000Credit

VaR=1,000,000-20,000=980,000Key

Indicators28-203PortfolioCreditVaREstimationofPortfolioCredit

VaRρ=0(numberofdefaultsisbinomially

distributed)Givenaportfoliowithavalueof$1,000,000and50credits.Eachcreditisequallyweightedandhasaterminalvalueof$20,000eachifnodefaultoccurs.EachcreditshasaPDofπandaRRofzero.WhatisthecreditVaRat95%confidencelevelifπis2%andthedefaultcorrelationis0?(the95thpercentileofthenumberofdefaultsbasedonthisdistributionis

3)?EL=1,000,000×2%=

20,000WCL(95%)=3×20,000=

60,000Credit

VaR=60,000-20,000=40,000Key

Indicators29-203EffectofGranularityonCreditVaRWhentheportfoliobecomesmoregranular,thatis,containsmoreindependent

credits,

each

of

which

is

a

smaller

fraction

ofthe

portfolio.TheCreditVaR

is,naturally,higherforahigherprobabilityofdefault,giventheportfoliosize.Butitdecreasesasthecreditportfolio

becomes

moregranularforagivendefaultprobability.Butthathasan

importantconverse:ItishardertoreduceVaRbymakingtheportfolio

moregranular,ifthedefaultprobabilityis

low.Eventually,foracreditportfoliocontainingaverylargenumber

ofindependentsmallpositions,theprobabilityconvergesto100

percentthatthe

credit

loss

willequal

the

expected

loss.

The

portfolio

then

has

zerovolatilityofcreditloss,andtheCreditVaRis

zero.Capital

StructurePDσ2=PD×(1?

PD)StepstoDeriveEconomicCapitalforCredit

RiskExpectedLosses

(EL)UnexpectedLosses

(UL-Standalone)UnexpectedLossContribution

(ULC)Economic

CapitalELandUL(instatistical

terms)EL=PD×EA×

LRUL=

EA

× PD

×σ2 +LR2×

σ2LR PDWhereσLR=standarddeviationofthelossrate

LRσPD=standarddeviationofthedefaultprobability

PD30-203Capital

StructureExampleSupposeXYZbankhasbookedaloanwiththefollowing

characteristics:totalcommitmentof$2,000,000,ofwhich$1,200,000is

currentlyoutstanding.

The

bankhas

assessed

an

internal

credit

rating

equivalenttoa1%defaultprobabilityoverthenextyear.Drawdownupon

defaultisassumedtobe75%.Thebankhasadditionallyestimateda40%lossgivendefault.ThestandarddeviationofEDFandLGDis5%and30%,respectively.Calculatetheunexpected

lossforXYZbank.EA=1,200,000+800,000×75%=

1,800,000UL=

1,800,000

× 1%×30%2+40%2×5%2=

64,90031-203Capital

StructureUnexpectedLoss

ContributionULMCi

==??????LP 1??????Li

2ULP×

P

????

UL2??????Li=12ULP×i=

j=????????????????=????=????

∑n1∑n

1

ρijULiULj ∑????1

????????????

????????????????????????TotalContributiontothePortfolio’s

ULnULP=?ULMCi×

ULii=1ULCi=ULMCi×ULi

=i=

∑n1ULj×

ρijULP×

ULi32-203Capital

Structure33-203Economic

CapitalAsdefinedpreviously,theamountofeconomiccapitalneededisthe

distance

between

the

expected

outcome

and

the

unexpected

outcomeatacertainconfidence

level.Unexpected

loss

is

translated

into

economic

capital

for

credit

risk

inthree

steps:First,thestandaloneunexpectedlossis

calculated.Then,thecontributionofthestandalone

ULtotheULofthebankportfoliois

determined.Finally,thisunexpectedlosscontribution(ULC)istranslated

intoeconomic

capital.Capital

StructureEconomic

CapitalEconomicCapitali=ULCi×

CMEconomicCapitalP=ULp×

CMCM=capital

multiplier34-203Capital

Structure35-203ChallengestoQuantifyingCredit

RiskThisapproachassumesthatcreditsareilliquidassets.Sincethecreditriskofbankloansbecomesmoreandmoreliquid

andistradedin

thecapitalmarkets,avalueapproachwouldbemore

suitable.Thiswouldrequiremodelingthemulti-periodnatureofcredits

and,hence,

the

expected

and

unexpected

changes

in

the

credit

quality

oftheborrowers

(and

their

correlations).

The

more

precise

numerical

solutionsgetverycomplexandcumbersome.Therefore,almostallinternalcreditrisk

models

used

in

practice

use

only

aone-year

estimation

horizon.Althoughthisapproachconsiderscorrelations

atapracticablelevelwithin

the

same

risk

type,

it

assumes,

when

measuring,

thatallother

risk

components

(such

as

market

and

operational

risk)are

separated

and

are

measured

and

managed

in

different

departments

within

the

bank.Exercise

1SupposeBankZlendsEUR1milliontoXandEUR5milliontoY.Overthenextyear,thePDforXis0.2andforYis0.3.ThePDofjointdefaultis0.1.Thelossgivendefaultis40%forXand60%for

Y.Whatis

the

expected

loss

ofdefault

in

one

year

for

the

bank?EUR0.72

millionEUR0.98

millionEUR0.46

millionEUR0.64

millionAnswer:

B2021CFA&FRM

36-203CreditRiskMeasurement37-203Topic1:Probabilityof

DefaultBasicApproachesusedtoPredicting

DefaultRating

SystemMeasurementfromMarket

PricesExponential

DistributionSingleFactor

ModelOther

ModelsBasicApproachesusedtoPredicting

Default38-203Experts-Based,Statistical-basedandNumerical

ApproachesExperts-BasedStatistical-BasedHeuristicandNumerical

ApproachStructuralApproachesandReduced-Form

ApproachesStructural

Approaches:

based

on

economic

and

financial

theoreticalassumptionsdescribingthepathtodefault.Modelbuildingisanestimateoftheformalrelationshipsthatassociate

therelevantvariablesofthetheoreticalmodel.(e.g.,

Merton)Reduced-Form

Approaches:

the

final

solution

is

reaches

using

the

moststatisticallysuitablesetofvariables

anddisregardingthetheoreticalandconceptualcausalrelationsamong

them.Rating

System39-203KeyFeaturesofaGoodRating

SystemMeasurabilityand

VerifiabilityObjectivityand

HomogeneityRatingAgencies’Assignment

MethodologiesMoody’s

releases

mainly

issues

ratings

and

far

less

issuers’

rating.S&Pconcentratesonprovidingacreditqualityvaluationreferredto

theissuer,

despite

the

fact

that

the

counterparty

could

be

selectively

insolventonpubliclistedbondsoronprivate

liabilities.FITCH

adopts

an

intermediate

solution,

offering

an

issuer

rating,

limitedtothepotentialinsolvencyonpubliclylistedbonds,without

consideringthecounterparty’sprivateandcommercialbank

borrowings.Rating

released

by

the

three

international

rating

agencies

are

not

directlycomparable.SpecificityRating

System40-203FromBorrowerRatingsto

PDInitialRatingAverageCumulatedAnnualDefaultRatesattheEndofEachYear

(%)Year

1Year

2Year

3Year

4Year

5Year

6Year

7Year

8Year

9Year

10Aaa0.000.000.000.000.000.000.000.000.000.00Aa10.000.000.000.000.000.000.000.000.000.00Aa20.000.000.000.000.000.000.000.000.000.00Aa30.000.000.000.000.000.060.170.170.170.17A10.000.000.000.000.040.060.060.060.060.06A20.050.110.250.350.460.520.520.520.520.52A30.050.190.330.430.520.540.540.540.540.54Baa10.210.490.760.900.951.041.261.581.661.66Baa20.190.460.821.311.661.982.212.352.582.58Baa30.390.931.542.213.003.423.854.334.494.49Ba10.431.262.112.493.163.653.683.683.683.68Ba20.771.712.814.034.785.065.456.487.5310.16Ba31.063.015.798.5210.2411.7613.2514.6716.1217.79Rating

System41-203Transition

MatrixRating

agencies

also

assess

changes

in

ratings.

Probability

estimates

aresummarized

in

transition

matrices,

which

show

the

estimated

likelihoodofaratingchangeforacompanywithinaspecifiedtime

period.One-YearFinalRating

Class(%)AaaAaABaaBaBCaaCa-CDefaultWRInitialRating

ClassAaa89.17.10.60.00.00.00.00.00.03.2Aa1.087.46.80.30.10.00.00.00.04.5A0.12.787.54.90.50.10.00.00.04.1Baa0.00.24.884.34.30.80.20.00.25.1Ba0.00.10.45.775.77.70.50.01.18.8B0.00.00.20.45.573.64.90.64.510.4Caa0.00.00.00.20.79.958.13.614.712.8Ca-C0.00.00.00.00.42.68.538.730.019.8Rating

SystemMeasurementofPDinRating

SystemCumulativeDefault

ProbabilityProbabilitythataborrowerwilldefaultoveraspecifiedmulti-year

period.kPDcumulated

=DefiNamestk42-203t+k

tNames:thenumberof

issuersDef:

the

number

of

names

that

have

defaulted

in

the

time

horizonMarginalDefault

ProbabilityProbabilitythataborrowerwilldefaultinanygiven

year.PDmarg=PDcumulated?

PDcumulatedRating

SystemMeasurementofPDinRating

SystemForwardProbability(ContingenttotheSurvival

Rate)t,t+kPDForw

=Deft+k?DeftNames

survivedtt,t+kSurvival

RateProbabilityaborrowerwillnotdefaultoveraspecifiedmulti-year

period.SRForw

= 1?

PDForwt43-2031?

PDcumulatedi=?

SRForwt;t+kti=1Rating

SystemMeasurementofPDinRating

SystemAnnualizedDefaultRate

(ADR)If

itis

necessary

to

price

a

credit

exposed

transaction

on

a

five

year

timehorizon,

itis

useful

to

reduce

the

five-year

cumulated

default

rate

to

anannualbasisforthepurposesof

calculation.t1?

PDcumulatedi=?

SRForw=(1?ADRt)ttt44-203i=11?

PDcumulated=

e?ADR×tRating

System45-203MeasurementofPDinRating

SystemExampleYears012345names1000990978965950930default1022355070PD(cumulated,%)1.002.203.505.007.00PD(marg,%)1.001.201.301.502.00PD(forw,%)1.001.211.331.552.11SR(cumul,%)99.0097.8096.5095.0093.00SR(forw,%)99.0098.7998.6798.4597.89ADR(discrete,%)1.001.111.181.271.44ADR(continuous,%)1.011.111.191.281.45Exercise

1Default

ProbabilityRating3

year5

yearAAA0.05%0.15%AA0.22%0.48%A0.30%0.72%BBB0.92%1.98%BB6.91%11.83%B20.37%28.00%CCC31.63%40.15%

Answer:

C46-203Usethefollowingtabletoanswerthequestionblow.Whichloanbelowhasthehighestexpectedcreditloss?(Assumethatalloftheloansaredueatmaturitywithoutamortizationandrecoveryrateis

zero).A 3-year loan of $50,000,000 to acounterpartywithacreditratingof

“A”.A 5-year loan

of $1,500,000 to acounterpartywithacreditratingof

“BB”.A 5-year loan of $40,000,000 to acounterpartywithacreditratingof

“AA”.A 3-year loan of $20,000,000 to acounterpartywithcreditratingof

“BBB”.Exercise

2Asaresultofthecreditcrunch,asmallretailbankwantstobetterpredictandmodelthelikelihoodthatitslargercommercialloansmightdefault.

It

is

developing

an

internal

ratings-based

approach

to

assess

itscommercialcustomers.Giventhisone-yeartransitionmatrix,whatistheprobabilitythataloancurrentlyratedatBwilldefaultoveratwo-year

period?A. 17.50%B. 20.0%C. 21.1%D. 23.5%

Answer:

D47-203RatingatBeginning

ofPeriodRatingatEndof

PeriodABCDA0.900.100.000.00B0.000.750.150.10C0.000.050.550.40MeasurementfromMarket

PricesInferPDfromCorporateBond

PricesRisk-Neutral

PDDefaultPayoff=

$1×RRP1–

PDt=

0NoDefaultPayoff=

$1t=

1PDp

=$1 $1×PD×RR+$1×(1?PD)1+YTM

=?PD

=(1+

Rf)1 YTM?

Rf

LGD 1+

YTM?YTM?Rf≈PD×

LGD48-203MeasurementfromMarket

Prices49-203InferPDfromCorporateBond

PricesCreditSpread–DVCS(spread

‘01)The

spread

’01

is

analogous

to

the

DV01.

It

measures

the

price

changeimpliedbyaonebasispointchangeinthecredit

spread.Z-spreadisthespreadthatmustbeadded

totheLIBORspotcurve/government

bond

curve

to

arrive

atthe

market

price

of

the

bond.We

calculate

the

DVCS

by

re-pricing

the

bond

after

shocking

the

z-spread.Example:currentbondprice:92,currentz-spread:

207;scenario1:bondprice:91.93,