剑桥风险研究中心-利用现实世界场景提高私人投资组合的弹性（英）

CambridgeCentreforRiskStudies

abrdn

USINGREALWORLD

SCENARIOSTOIMPROVE

THERESILIENCEOF

PRIVATEINVESTMENT

PORTFOLIOS

UsingRealWorldScenariostoImprovetheResilienceofInvestmentPortfolios

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UsingRealWorldScenarios

toImprovetheResilienceofPrivateInvestment

Portfolios

"Historicalperformanceisnoguaranteeoffutureresults":Althoughanalysisofexperiencedatahelpsinvestmentmanagersassesshowtheirportfoliosandassetswouldhaveperformedagainstpastcrises,thenextcrisiswillbedifferent.Improvinginvestmentstrategiesagainstfuturerisksrequirestestsagainstscenariosoflikely-andunlikely-eventsacrossawiderangeofpotentialcauses.Real-worldscenariosbuildhypothesesaboutplausibleextremeeventsofthenear-termfuture,basedonscientificevidence,andusesthemtoassesshowtheycouldaffectinvestments.Usingreal-worldscenariosimprovestheresilienceofinvestmentstrategiesandprovidesbetterassessmentofriskpremiumsinassetpricing.

1ExecutiveSummary

Aftertheglobalfinancialcrisisof2008/9(GFC),privatemarketshavecontinuedtoexpandatatremendouspaceasinvestorsareincreasinglyattractedtotheprivateassetclassbyarangeofbenefitssuchasbetterreturnscomparedtotraditionalassetclasses,alowercorrelationwithotherassetsandeffectiveportfoliodiversification.Spanningprivateequity,infrastructure,naturalresourcesrealestateandprivatecredit,privatemarketshavewitnessedaperiodofphenomenalgrowth.Investorsarecommittingtoprivatemarketsintheirsearchforstableincomeand/orsuperiorreturns.

Thedynamicnatureofprivateinvestments,however,employsmultipleleverstodrivevalue,leadingtoasignificantlevelofidiosyncrasy,whichischallengingtomeasure.Lookingatthecorporatespace,thisidiosyncrasymanifestsitselfincorporatestrategy,M&Astrategy,productdevelopments,supplychain,technologyutilisationandfinancialleveragewhichareallbeingoptimisedtomaximisevalueinthemediumtolongterm.

AftertheGFCtherehasbeenareappraisalofinvestmentmodellingmethodsandanalyticalapproaches,particularlyinpublicmarkets.Thecrisisraiseddoubtthattheframeworkformeasuringriskinpublicmarketswasappropriateforportfolioscomprisingacombinationofpublicplusasignificantproportionofprivatemarketassets.Themaincriticismisthatreturnsinprivateassetsaremorevulnerabletolowprobability,highimpacttailrisksandarethereforeunlikelytobenormallydistributed.Thishasmadeitproblematictoapplytraditionalsystematicriskornon-diversifiableriskmeasurestoprivateportfoliosduetolimitedhistoricaldata.

Furthermore,itisdifficulttoformrobustconclusionsabouthowassetsperformunderdifferentmacroeconomicscenarios.

Toprovideasolution,thisprojectisanendeavourtoincorporatescenarioapproacheswiththelatestdevelopmentsinenterpriseriskmodellingtechniquesdevelopedbytheCambridgeCentreforRiskStudies(CCRS).Theyhaveresearchedmarketandmacroriskstomeasureportfolioexposurestoriskfactorsthatcanimpacttheindividualconstituentsofaninvestmentportfolio,oftendescribedasidiosyncraticrisks.

Anenterprisevaluationmodelframeworkhasbeendevelopedwhereconstituentscanbeshockedwhencalibratedtoascenariotomaketheframeworksystematicacrossmacroandmarketfactorsand,moresignificantly,theidiosyncraticcontributions.UtilisingamethodologycombiningCambridgescenariosanddigitaltwinsrepresentingportfoliocompanies,theportfolio-wideimpactofasuiteofscenarioscanbeassessedbymeasuringtheextentofpossiblelossesinfirms’discountedcashflow,wherethedeltabetweenthebaselineandmodelledcashflow,acrossallscenarios,iscalledEarningsValueatRisk.Thisenablesinvestmentmanagerstomeasureandprioritisetheriskexposureanddecidetheoptimalcourseofactionstomitigateandremediatetheriskontheirownportfolios.

Thispaperservesasanarchetypalmethodologythatprovidesabasisforfurtherresearchonintegratingamulti-dimensionalriskmanagementparadigmintotheinvestmentdecision-makingprocessforprivatemarketsassets.Ascenariostresstestingapproachcanprovideacomplementarytoolthathelpsassessingandconfrontingtheseuncertaintiesandthereforecontributingtowardstheviabilityofaportfolio.

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2Introduction

TheconceptspresentedinthisreportcovertheongoingresearchjointlyconductedbytheCambridgeCentreforRiskStudies(CCRS)andabrdnonimprovingtheresilienceofprivateinvestmentportfolios.Thebodyofliteratureaddressingriskmodellingofprivatemarketassetsisrelativelyscarcecomparedtothatofpublicmarketassets.Asaresult,assetstradedinprivatemarketshavebeentreatedinterchangeablywiththoselistedinpublicmarkets.Inthisprocess,therehasbeenlittlefundamentaldifferencebetweenadjustmentsmadetoaddresstheinherentcharacteristicsofprivatemarketassetsandriskstheunderlyinginvestmentscarryandthosemadetopubliccapitalmarketassets.Thisreporthighlightsthepotentialofusingrealworldscenariosasacomplementaryapproachtoclassicalefficientmarkethypothesisanddynamicequilibriummodels.

Wedefineprivatemarketportfoliosasthoseconsistingofunlistedorprivatelyheldassetclassessuchasprivateequity,infrastructure,realestate,privatecreditandnaturalresources.Investmentsinprivatemarketshavehistoricallybeentaintedwiththeperceptionthattheseassetshavenotalwaysbeeneasilyaccessible.Asreturn-starvedinvestorsarelookingforopportunitiestoimprovetheirportfolioreturnsinthelowyieldenvironment,however,privatemarketassetsareincreasinglyviewedasanessentialandcorepartoftheirassetallocationandoverallinvestmentstrategies,addingsignificantvaluetotheirportfoliosbyofferingbetterreturnpotentialsthanconventionalinvestmentoptions,aswellasdiversificationandvolatilitymitigationbenefits.

Modellingandassessingtherisksofprivatemarketinvestmentportfoliosisachallenging,especiallyregardingeventsinthetailofdistributions.TheCambridgeTaxonomyofBusinessRisksidentifiesbroadcategoriesofcausalthreatsthatcouldpotentiallycauseasocialoreconomiccrisis.1Thiscould,inturn,havethepotentialtoimpactthereturnsofinvestmentportfoliosandindividualassets.Usingrealworldscenariostoquantifytheriskassociatedwithaninvestmentportfolioisaneconomicmethodofcapturingsomeofthetailriskthataportfolioisexposedto.Wetakedatafrom

1CCRS(2019).

2See,forexampleTheEconomist,July18,2009.

historicaleventstoparametrisethemodelallowingforarobustmethodofriskanalysis.Thismethodologycanbenefitanassetmanagerbyhighlightingtheeventsthatposeaseriousthreattotheirportfolio,aswellasoutliningthekeydriversbehindthethreat.Thistypeofmodellingisusefulforhighimpact,lowprobabilityeventsthatconstitutetailrisks,whicharenoteasytodetectormeasurewithinthetraditionalriskmodellingframeworkasthesemodelsassumenormalityasadefault.

Thisreportpresentstheunderlyingconceptsofusingrealworldscenariosasacomplementtostandardriskmanagementpracticesforstresstestingprivatemarketinvestmentportfolios.Thekeytopicsinclude:

•Reviewoftraditionalriskmodels

•Limitationsoftraditionalriskmodels

•Taxonomyofportfoliorisks

•Scenariostosupportstresstestingincludingtheirdevelopmentandapplicationmethodology

•Scenarioapplicationstoprivatemarketportfolios.

3PortfolioTheorySinceGFC

TheGFCandthefailureofmanyinvestmentportfolioriskmanagementtoolstoanticipateandmanagethemeltdownhasledtoageneralreappraisalofinvestmentmodelsandanalyticalapproaches.

Thecreditcrunchandassociatedeconomiccrisisthatfollowedgeneratedalargevolumeofcommentaryandinterpretation,andconsiderablequestioningofconventionaleconomictheory.2Macroeconomicmodelsreliedonbyseveralcentralbanks,knownas‘dynamicstochasticgeneralequilibrium’(DSGE)models,failedtoanticipatethedownturn.Amongotherinitiatives,ittriggeredamovementto‘ReinventEconomics’.

Thecritiqueofclassicaleconomictheoryquestionsthebasicassumptions,principallythe‘EfficientMarketHypothesis(EMH)’and‘dynamicequilibrium’.Suchmodelsarefelttobevaluableformanypartsofeconomicdecision-makingbutpooratunderstandingfinancialcrises.Somecommentatorshavesuggestedthattraditionaleconomics,developedduringtheearly19thCentury,isbasedonapoorparadigm,thermodynamics,inwhichsteady-statesareeventuallyachieved.3AnumberofauthorshighlightthefallacyoftheEfficientMarket

3SeeBeinhocker(2007),pp21-43‘TraditionalEconomics:AWorldinEquilibrium’.

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Hypothesisinhavingnoroomforassetpricebubblesorbusts–thetheoryinsiststhatmarketsarealwayscorrectlypricedandthatbubbleshavetobenothingmorethanmarketsrespondingtochangingfundamentals.4

3.1FatCatastropheTails

Theissueforseveralanalystsisthatthetailsofthedistributionsarefatterthanmightbeexpectedfromtraditionalanalysistechniques.Asearlyasthe1960sthemathematicsofMandelbrotdemonstratedthatdistributionsofmarketpricefluctuationshavemuchfattertailsthantraditionallyexpectedbuttraditionaleconomistshavetendedtopursuemathematicalcharacterizationsbasedon‘randomwalks’(i.e.information-freerandomnesswithtrends).5Theseleadtounderestimationsofthelikelihoodofmajormarketmovements.TheeconomistGeneStanleyofBostonUniversitydemonstratedthatamarketdipoftheseverityofthe1987‘BlackMonday’hasalikelihoodof10-148intraditional‘randomwalk’mathematics.6RobertMerton,oneoftheNobel-prizewinningarchitectsoftheBlack-Scholesmodel,isquotedin1998onthedayafterLong-TermCapitalManagementlost$4.4Bnassaying“accordingtoourmodelsthisjustcouldnothappen”.7Asimilarquoteisattributedtoanunnamedchieffinancialofficerinoneoftheworld’slargesthedgefunds,afterithadsufferedhugelossesin2008assayingithadsufferedadverse“25-standarddeviationevents,severaldaysinarow”accordingtotheirmodels.8

3.2Theyweren’tdesignedasCatastropheModels

Tobefair,themodelsthatweresoheavilycriticisedwerenotdesignedtoestimatecatastropherisk.TheDSGEmodelsusedbycentralbanksweredevelopedtoinformeconomicandmonetarypolicyandhaveperformedwellduringperiodsoffinancialstability.Assetpricingmodelsingeneralhavebeengreataidstoinvestmentmanagementandhavethemselves“createdmarkets”.Economicmodelsbasedontheoreticalprincipleswereusedfromthe1970sonwardsas‘engines’todrivemarketchangeratherthanasobjective‘cameras’tosimplyreproduceempiricalfacts,9andassuchthesemodelsalteredthe

4Cooper(2008)isonekeycriticoftheefficientmarkethypothesis,inhisbookTheOriginofFinancialCrises:CentralBanks,CreditBubblesandEfficientMarket

Fallacy.

5SeeMandelbrot(2008)andBeinhocker(2007)p179-181.

6PresentationbyH.EugeneStanleyataconferenceonTheEconomyasanEvolvingComplexSystem,SantaFe

Institute,Nov16,2001inBeinhocker(2007)p180.

7‘HowtheEggheadsCracked’byM.Lewis,NewYorkTimesMagazine,Jan24,1999pp24-77.

8Cooper(2008)p10.

9MacKenzie(2006):AnEngine,NotaCamera:HowFinancialModelsShapeMarkets.

marketstheyrepresentedthrough,forexample,enablingfuturesandderivativestrading,whichtodayaremajorcomponentsofthefinancialmarket.

FinancialassetpricingmodelshavebeenunderscrutinysincetheBlack-Scholes-MertonmodelwaswidelyblamedforthefailureofLongTermCapitalManagementin1998.10Thesemodelshaveevenbeenblamedforthebehaviourofentiremarkets–whenmanytradersareusingsimilarmodels,theytendtomakesimilardecisions.Theclaimisthatthishasincreasedthecoordinationofactivity(‘flockbehaviour’)andthecorrelationofassetpricesacrossmarkets,assetclasses,andgeographiessignificantlyoverthepasttwodecades.

Bankrunsarecitedassimilarexamplesofsharedbeliefsfuelling‘mobpsychology’inthegeneralpopulation.TheincreasedspeedofinformationflowsthroughthemarketprovidedbytheInternet,andtheubiquityofmodelledviewsofpricingaresignificantfactorsinincreasedcorrelationandthespeedwithwhichmarketcrashescannowoccur.Theconceptofcoordinatedactionsbyindividualsfacilitatedbyextraneousfactorswhicharenoteasytoexplainis(rathercharmingly)referredtobyfinancialanalystsas‘sunspots’.11

3.3AlternativeEconomicTheories

Alternativeeconomictheorieshavebeenbeingproposed,includingMandelbrot’s‘TurbulentMarketswithMemory’,12Minsky’s‘FinancialInstabilityHypothesis’,13andtheemergingfieldof‘ComplexityEconomics’.14Moderntheoristssuggestthat‘punctuatedequilibrium’orgrowthcyclesofboom-and-bust,maybeinherentpropertiesofahealthygrowingeconomy.Intheseviewsofeconomics,thecharacteristicsofthefinancialsystemitselfiswhatdefinesthefrequencyandseverityofcrises:i.e.financialcatastrophesarisefrom‘endogenous’characteristicsofthecomplexsystem,aswellas,andperhapsevenmorethan,‘exogenous’externalshocks.

3.4ComplexityEconomics

Thesealternativetheoriesproposeconsideringeconomicactivityasacomplexadaptivesystem.Some

10SeeMacKenzie(2006)pp218-242foranexaminationoftheLTCMcasestudy.

11Allen&Gale(2008)‘Theroleofsunspots’p76in

UnderstandingFinancialCrises.

12Mandelbrot&Hudson(2008).

13Minskyfirstrefutedtheefficientmarkethypothesiswithhis‘FinancialInstabilityHypothesis’in1936,whichis

adaptedbyCooper(2008)asabasisforimprovingcentralbankpolicy.

14OutlinedbySornette(2003)inWhyStockMarkets

Crash:CriticalEventsinComplexFinancialSystems.

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evensuggestthatabetterconceptualmodelforeconomicactivitymightbebiologicalevolution.15Theseideasareembracedundertheterm‘ComplexityEconomics’orasanewmanifestationofalongstandingbranchoftheorytermed‘BehaviouralEconomics’.16Theeconomyisseenasacomplexsystem,andamarketcrashisacatastrophicfailure.

Evenwithoutanunderlyingtheoreticalbasis,theplausibilityandimpactofextremeshockscanbeassessedthroughscenariosthatincorporatereal-worldcharacteristicsofcausalprocessesandinterconnectivity.

4ThePastisNoGuidetotheFuture

Statisticaldataofpastyieldsandassetperformanceareusedtocalibratemanyofthetraditionalmodelsofinvestmentriskpremiums.Reliabletradingdataisavailabledatingbacktothe1970s-around50years.Thatperiodhasseenmanyextremeevents,crises,externalities,andblips.Itcouldbeassumedthatthemostextremeeventsobservedinthatperiodrepresentthe‘1-in-50’annualextreme.Butwhataboutthe‘1-in-100’–canwejustextrapolateusinganassumptionaboutthedistributions?Philosophicallywedonotbelievethatthepast50yearscontainsenoughextremeexamplestofullypopulatethetailriskfromstatisticalexperience.Thereisliteratureconcernedwithhowtomakeallowancefor‘strategicsurprise’andnewtypesofcrisesthathavenotbeenseenbefore,referencing‘BlackSwans’;17‘DragonKings’,18‘UnknownUnknowns’,19and‘Non-ModelledRisks’.20Manyorganizationsexpendsignificantresourcestomonitor‘emergingrisks’andthethreatstheyface,asawayoftryingtoanticipatepotentialnewthreatsthatcouldtriggerdevaluationevents.Ourapproachistoconsiderauniverseofpotentialthreats,whichallowsforcompletelyunforeseensurprise,butbyexhaustiveanalysisandresearchtocreateauseabletaxonomyofcausalissuesthathaveplausiblecapabilityofcausingeventsinthenextseveralyears.Eachofthesearethentestedwiththedevelopmentofascenariothatenablesaportfoliostresstestthatillustratesthosethreats.

5LimitationsofTraditionalRiskModels

Whenanalysingportfolios,differentmodellingtechniquescanbeemployedtoprovideaviewofrisksassociatedwithit.Commonlyadoptedriskmanagementtechniquesaredesignedtoevaluatea

15Beinhocker(2007)apes(asitwere)Darwin’sTheOriginofSpeciesintitlinghisbookTheOriginofWealth.

16TheEconomistdescribesthestateoftheartofapplyingpsychologystudiestoeconomicsundertheumbrellaofBehavioralEconomics,inFinancialEconomics:

EfficiencyandBeyond’,p73-74,July18,2009.

portionoftherisk,butnotallofit.Forassetmanagers,adelicatebalancemustbestruckbetweenensuringthataninvestmentisprofitablewhileaccountingforenoughrisktoensurethatasufficientbuffercanbeputinplacetoprotectthem.Typically,astatisticalapproachistakentoassesstheriskassociatedwithaninvestment,forexamplethelikelihoodofaninvestmentfailing.Bysettingarangeoflikelihoodsinwhichassetmanagersareconfidentininvesting,thisbuildsariskappetite.Howeverstatisticalviewsmaycontaininsufficientinformationaboutthepotentialforfailure.Whenamajordevaluationeventoccurs,itcanhavefarreachingeffects,astailriskshavepotentialtobebeyondanassetmanager’sriskappetite.

Asdescribedabove,theGFCisanexampleofsuchahighly-correlatedcatastrophiceventoutsideofstatisticalbounds.Atthetimevalue-at-riskmodelscaptured99%oftheriskforabundleofsecurities.Itdidnottakeintoaccountthe1-in-100(year)eventwhichinthiscasewasamassdefaultonmortgagesintheUShousingmarket.Fromamodellingperspective,the1-in-100eventmayhavebeenoverlookedwhenthesecuritiesweretraded,withpeopleunder-pricingthetailrisks.Investorsandregulatorshavelearntsomelessonsandnowapplybetterriskmanagementprinciples.Forexample,therearenowstrictrulesinplacetolimitspeculativeinvestmentsanddangerouscorporateculturedrivingaggressiverisk-taking.Theserulesprovideagreaterlevelofmarketoversightandtighterrestrictionsondisclosurepolicies.

Manymodellingmethodsarenotdesignedtomodelextremetailrisks.Macroeconomicgeneralizedequilibriummodelscanbestressedwithmoderatevariations,butcanfailtoresolvewhenthevariationsexceedthehistoricalrangeofobservedvariation,particularlyinthecaseofhighlyimprobablebuthighlyimpactfulaccidentsornaturalphenomena,i.e.acatastrophe.

Inacontextofprivatemarkets,investorshadinvestedinavarietyofunconventionalassetclassesthattheythoughtofferedthemdiversificationfromequities,priortotheGFC.Inthisevent,theyweredisappointedtodiscoverduringthe2008–09equitybearmarket,thisdiversificationwaslargelyillusory.Forthatreason,webelievethattheassetclassesthatprovidethemostrobustdiversificationfromequitiesarethosewhoseunderlyingcashflowsareinsensitive

17Taleb(2010).

18Sornette(2009).

19Rumsfeld(2002).

20ABI(2014).

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tothebusinesscycle.Forexample,inaprivatemarketuniverse,infrastructureisanassetclassthatcanbeeconomicallyinsensitivethuslesscyclical.Manyunderlyinginfrastructureassetssuchasenergygeneratingfarms,schools,hospitalsandutilitieslikeelectricitygridshavecashflowsthataredrivenbylong-termgovernment-backedcontractsorsubsidies,furtherlinkedwithinflation.

MorerecentlyduringtheCOVID-19marketturmoilin2020,lookingatsocialinfrastructureforexample,wecanseehowwellitfaredwhenequitiesandrealestatewereexperiencinglargepricedeclines.Intermsofareturnsperspective,mostinvestorsrelyexclusivelyonassetsthatarelistedonpublicmarkets,buthigherreturnsareoftenavailablefromunlistedorprivatelyheldassetslikeprivateequity,infrastructure,directproperty,privatecreditandnaturalresources.Privateassetstypicallyofferhigherreturnsthantheirlistedversionsbecauseinvestorsreceivean‘illiquiditypremium’incompensationforlosingtheabilitytoreleasetheircapitalatashortnotice.Thispremiumtypicallyadds2–4%toreturns,dependingontheassetclass.Strongdemandforprivatemarketsinrecentyearsindicatesthatthispremiummaybenowatthelowendoftherange,however,giventhelowexpectedreturnselsewhereoveralonghorizon.

Investorssometimesmistakenlybelievethatbecauseprivateassetsareilliquidthismeansthattheygetnocashreturnintheshortterm.Infact,manyprivateassetsofferastableincomereturnduringtheperiodtheyareheld.Oneofthebiggestchallengesforinvestorsinprivateassetsisidentifyingandaccessingthebestinvestmentopportunitiesgivenitsreturnandriskappetite.Thedifferenceinperformancebetweentopandbottom-quartilemanagersismoresignificantforprivateassetclassesthanitisforlistedmarkets.Hence,managerselectioniscriticalasthefundswiththebesttrackrecordscanoftenbehardtoaccess.

Intermsofmarkettransparencyoftheprivatemarkets,therehasbeengrowingtransparencyinprivateassets,assuggestedbyHudsonandDeSilva(2016),makingthemmoreviableduetodiversificationeffects,yield,andrisktolerance.Ingeneral,thetrendisthatbetterinformationcomingoutofprivatemarketsisallowingmarketstobemoreliquid.However,theproblemremainsthattherearestillgapsinthereportingperiodsasprivateassetstakeadiscreteapproachtopublishinginformation.Unliketheusualmethodsofmodellingrisksforpublicassets,theyacknowledgethattheseprivateassetsaremorevulnerabletolowprobability,highimpacttail

21Rebonato(2010)

risks.Thissuggeststhatadifferentriskmodellingapproachisrequiredforthesetypesofportfolios.

6TaxonomyofPortfolioRisks

Singlevariablestresstests(e.g.asuddenreductionininterestrate)canbeappliedtoaportfoliotoensurethataninvestmentisrobustenoughtoweatherashock.Howeverreal-worldshocksrarelyaffectasinglevariable.Theunderlyingcauseofthereductionininterestratewillalsoaffectothereconomicvariables,anddependingonthecause,canhavequitediverseeffects.Inordertoprepareforthetailrisksitisnecessarytotakecombinationsofextremeevents,whichcanhavemultiplestressvariablesaffectinganinvestmentportfolio.Theinterrelationshipbetweentheimpactfulvariableschangeswiththenatureoftheunderlyingrealworldcauseoftheshock.

Rebonatoexploresthedifficultyofstresstestingrisksandarguesfor‘coherence’instresstestvariablesconsistentwithusingrealandhypotheticalscenarios.21Event-treeapproachesofrandomlystressingmultiplevariablesbecomerapidlyunfeasiblewithmorethanahandfulofvariables,tobranchouteveryeventthatcanaffectaportfolio,especiallyatthesametime.Insteadwefocusonspecificeventsmodelledafterrealworldscenarios.

Amoregroundedapproachtakesanunderstandingoftheuniverseofpotentialexogenousandendogenousshocksandabroadevaluationofthecausaldriversoftheseshocks.Theunderlyingcausesofsystemicriskswehavepreviouslytermed‘econotagions’.

CCRShasreviewedthelandscapeofrisktoattempttoidentifythebroadcategoriesofcausalthreatsthatcouldpotentiallycauseasocialoreconomiccrisiswiththepotentialtoimpactthereturnsofinvestmentportfoliosandindividualassets.

Thisstudy,ongoingsince2014,hasinvolvedmultipleresearchapproachesandhasresultedintwopublications.Identifyingthreatsinvolvedanextensivehistoricalreviewofcausesofsocialandeconomicdisruptionoverthepastthousandyears.Thiswasaugmentedwithareviewofcatastrophecataloguesanddatabases,aprecedentreview,astudyofcounter-factualtheories,andapeerreviewprocess.

Figure1:Cambridgetaxonomyofbusinessrisks,v2.0.22.

22CCRS(2019

Figure1showstheCambridgeTaxonomyofBusinessRisks.Itisorganisedinahierarchyofcausalsimilarity,into6PrimaryClasses,37Families,and170RiskTypes.Thestructurecanbefurthersubdividedintomoregranulartypesasrequired.Thisstructureprovidesauniversefromwhichtoselectscenariosofinteresttostressaportfolio.

Forexample,thegeopoliticalclassofscenariosconsiderstheriskassociatedwithnotonlytherelationsofacompanytoagoverningbody,