Model Risk - Identification, Measurement and Management

537 Pages·2010·5.527 MB·English

by  Daniel Rösch, Harald Scheule

The first years of the 21st Century saw the Chapters address: M
financial industry continue to pour vast • Sensitivity of regulatory and od Model
resources into building models to measure economic capital to market stress el
financial risks. Yet, as the financial crisis that • Systematic risk in a CDO Ris
began in 2007 has shown, these models’ portfolio k

predictions were often being used without • Transmission of macro shocks E
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limitations; and understanding of the context in • Cashflows from derivative y

which they were developed. The consequences portfolios D
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of model risk have been clear to see in the • Adequacy of market risk models n
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financial turmoil. • A new concept of potential l
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market risk ö
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Drawing on experiences and data from ch Identification,

the financial crisis, Model Risk: Identification, a
Measurement and Management provides detailed To date, model risk has lacked a clear nd Measurement

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analysis of the shortcomings in the design definition. This book explains the
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and application of modern risk models and different types of model risk; and ra and Management
offers solutions for better understanding and illustrates these with experiences ld

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use in the post-crisis era. The book sets out from the current financial crisis. c
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how to include model risk into existing risk Model Risk stands out as the guide to e
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measurement frameworks solutions and how to better risk management in uncertain le EditEd By daniEl Rösch

build better models as a result. times. and haRald schEulE
Part one of the book begins by setting out
frameworks for model risk. Four subsequent
sections tackle the models financial institutions
use by risk type:
• Macroeconomic and Capital Models
• Credit Portfolio Risk Models
• Liquidity, Market and Operational Risk
Models
• Risk Transfer and Securitisation Models
PEFC Certified
This book has been
produced entirely from
sustainable papers that
are accredited as PEFC
compliant.
www.pefc.org
Model Risk

Model Risk
Identification,Measurement and Management
Edited by Harald Scheule and Daniel Rösch
PublishedbyRiskBooks,aDivisionofIncisiveFinancialPublishingLtd
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Contents
ListofFigures ix
ListofTables xv
AbouttheEditors xxi
AbouttheAuthors xxiii
Introduction xxxv
PARTI CONCEPTSANDSTOCHASTICFRAMEWORKSFOR
MODELRISK 1
1 DownturnModelRisk:AnotherViewontheGlobalFinancial
Crisis 3
DanielRösch;HaraldScheule
LeibnizUniversitätHannover;TheUniversityofMelbourne
2 FollowtheMoneyfromBoomtoBust 19
JorgeR.Sobehart
CitiRiskArchitecture
3 ModelRiskandNon-GaussianLatentRiskFactors 45
SteffiHöseandStefanHuschens
TechnischeUniversitätDresden
4 ModelRiskinGarch-TypeFinancialTimeSeries 75
CorinnaLuedtke,PhilippSibbertsen
LeibnizUniversitätHannover
PARTII MACROECONOMICANDCAPITALMODELS 91
5 MonetaryPolicy,AssetReturnDynamicsandtheGeneral
EquilibriumEffect 93
Kuang-LiangChang;Nan-KuangChen;CharlesKaYuiLeung
NationalChiayiUniversity;NationalTaiwanUniversity;
CityUniversityofHongKong
6 CapitalDivergence:SensitivityofEconomicandRegulatory
CapitalunderStress 137
OlegBurd
KfWIPEX-BankGmbH
v
MODELRISK
PARTIII CREDITPORTFOLIORISKMODELS 153
7 DiversifiedAssetPortfolioModelling:Sourcesand
MitigantsofModelRisk 155
SeanKeenan,StefanoSantilli,SukyulSuh;
AndrewBarnes,HuaiyuMa,ColinMcCulloch
GECapital;GEGlobalResearchCenter
8 TransmissionofMacroShockstoLoanLossesinaDeepCrisis:
TheCaseofFinland 183
EsaJokivuolle;MattiVirén;OskariVähämaa
BankofFinland;UniversityofTurkuandBankofFinland;
UniversityofTurku
9 ComparisonofCredit-RiskModelsforPortfoliosofRetail
LoansBasedonBehaviouralScores 209
LynC.Thomas;MadhurMalik
UniversityofSouthampton;LloydsBankingGroup
10 ValidatingStructuralCreditPortfolioModels 233
MichaelKalkbrener,AkwumOnwunta
DeutscheBankAG
11 AsymmetricAssetCorrelation:SomeImplicationsforthe
EstimationofProbabilityofDefault 263
PeterMiu;BogieOzdemir
McMasterUniversity;BMOFinancialGroup
12 ALatentVariableApproachtoValidateCreditRatingSystems 277
KurtHornik,RainerJankowitsch,ChristophLeitner,StefanPichler;
ManuelLingo,GerhardWinkler
WirtschaftsuniversitätWien;OesterreichischeNationalbank
PARTIV LIQUIDITY,MARKETANDOPERATIONALRISK
MODELS 297
13 ModellingDerivativesCashflowsinLiquidityRiskModels 299
StefanReitz
HochschulefürTechnikStuttgart
14 PotentialFutureMarketRisk 315
ManuelaSpangler,RalfWerner
DeutschePfandbriefbank
15 MarketRiskModelling:ApproachestoAssessing
ModelAdequacy 339
CarstenS.Wehn
DekaBank
vi
CONTENTS
16 EstimationofOperationalValue-at-RiskinthePresenceof
MinimumCollectionThreshold:AnEmpiricalStudy 359
AnnaChernobai;ChristianMenn;SvetlozarT.Rachev;StefanTrück
SyracuseUniversity;DZBankAG;UniversitätKarlsruhe,
FinanalyticaInc,UniversityofCaliforniaatSantaBarbara;
MacquarieUniversity
17 OperationalRiskandHedgeFundPerformance:Evidencefrom
Australia 421
RobinLuo,XiangkangYin
LaTrobeUniversity
PARTV RISKTRANSFERANDSECURITISATIONMODELS 435
18 IdentificationandClassificationofModelRisksin
CounterpartyCreditRiskMeasurementSystems 437
MarcusR.W.Martin
UniversityofAppliedSciences,Darmstadt
19 QuantifyingSystematicRisksinaPortfolioofCollateralised
DebtObligations 457
MartinDonhauser,AlfredHamerle,KilianPlank
UniversityofRegensburg
Epilogue 489
Index 493
vii

List of Figures
1.1 SeasonallyadjusteddelinquencyratesforallcommercialUS
banks 4
1.2 Through-the-cycle(TTC)modelandapoint-in-time(PIT)
creditriskmodel 5
1.3 Credit-portfoliolossdistributions 8
1.4 Volumeofcreditderivativetransactions 9
1.5 Buyerofcreditriskprotection 10
1.6 Sellerofcreditriskprotection 10
1.7 Averagematurityofnewcreditderivatives 11
1.8 Interestandprincipalimpairmentsofsecuritisations 12
1.9 Credit-portfoliolossdistributions 12
1.10 Spreadsensitivityofaseniortranche 13
1.11 Impairmentratesbyratingcategory 14
2.1 DistributionofnormalisedreturnsfortheS&P500Index 32
2.2 DistributionofnormalisedreturnsfortheDJIIndex 32
2.3 Evolutionofthemarginaldistributionofexcessreturns
p(ξ,t)forβ=1andη/θ=0.3 34
2.4 Evolutionofthemarginaldistributionoflogpricesq(χ,t)for
β=1andη/θ=0.3 34
2.5 Comparisonbetweenthefrequencyofnormalisedreturns
fortheS&P500IndexandEquation2.20fordifferenttime
horizonsfortheperiod1950–2009 35
2.6 Comparisonbetweenthefrequencyofnormalisedreturnsfor
theS&P500IndexandEquation2.20asafunctionofthe
reducedvariablewfordifferenttimehorizonsusingthe
samedataasinFigure2.5 36
2.7 Comparisonbetweenthefrequencyofnormalisedreturnsfor
theDJIIndexandEquation2.20fordifferenttimehorizonsin
theperiod1928–2009 37
2.8 Comparisonbetweenthefrequencyofnormalisedreturnsfor
theDJIIndexandEquation2.20asafunctionofthereduced
variablewfordifferenttimehorizonsusingthesamedataas
inFigure2.7 38
2.9 Comparisonbetweenthefrequencyofnormalisedreturns
fortheFTSEIndexandEquation2.20asafunctionofthe
reducedvariablewfordifferenttimehorizonsintheperiod
1984–2009 38
2.10 Comparisonbetweenthefrequencyofnormalisedreturnsfor
theNikkeiIndexandEquation2.20asafunctionofthe
ix