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CambridgeCentreforRiskStudies
CambridgeRiskFramework
FoodandOilPriceSpiralStressTestScenario
HIGHINFLATIONWORLDSTRESS
TESTSCENARIO
CambridgeCentreforRiskStudies
UniversityofCambridgeJudgeBusinessSchool
TrumpingtonStreet
Cambridge,CB21AG
UnitedKingdom
enquiries.risk@jbs.cam.ac.uk
http://www.risk.jbs.cam.ac.uk
December2015
TheCambridgeCentreforRiskStudiesacknowledgesthegeneroussupportprovidedforthis
researchbythefollowingorganisations:
TheviewscontainedinthisreportareentirelythoseoftheresearchteamoftheCambridgeCentreforRiskStudies,anddonotimplyanyendorsementoftheseviewsbytheorganisationssupportingtheresearch.
Thisreportdescribesahypotheticalscenariodevelopedasastresstestforriskmanagementpurposes.Itdoesnotconstituteaprediction.TheCambridgeCentreforRiskStudiesdevelopshypotheticalscenariosforuseinimprovingbusinessresiliencetoshocks.Thesearecontingencyscenariosusedfor‘what-if’studiesanddonotconstituteforecastsofwhatislikelytohappen.
FoodandOilPriceSpiralStressTestScenario
HighInflationWorld
Contents
1ExecutiveSummary4
2DefiningtheScenario8
3HighInflationasaFinancialCatastrophe12
4DefiningtheScenario15
5TheScenario17
6MacroeconomicAnalysis19
7ImpactonInvestmentPortfolio25
8MitigationandConclusions32
9Bibliography33
4
CambridgeCentreforRiskStudies
FoodandOilPriceSpiralStressTestScenario
HighInflationWorld
1ExecutiveSummary
Inthefollowingreport,wepresentanarrativeofhowglobalinflationarypressureoverseveralyearsimpactstheworldeconomyandfinancialmarkets.Thisprovidesabasisforaglobalenterprisetotestitsoperationalandstrategicmodel,asasteptowardimprovingitsresilience.Scenariosmoregenerallycanbeusedtocoverthespectrumofextremeshocks,suchasthoseproposedintheCambridgeTaxonomyofThreats,whichencompassesfiveclassesofbusinessrisk.1
HighInflationWorldScenario
Thisscenarioenvisionscostshocksinresponsetoshrinkingglobaloilsuppliesand,simultaneously,disruptionstocropproductionthatleadtoglobalfoodshortages.Theseinflationarydriverspersistovermanymonths,causinginternationaleconomicandhumanitarianpressures.
Theeconomicimpact,expressedaslostglobalGrossDomesticProductoverfiveyears,comparedwiththeprojectrateofgrowth(“GDP@Risk”),isbetween$4.9,$8and$10.9trillion,dependingontheseverityofthecommoditypriceshock.TheGreatRecessionof2007-2011,comparatively,sawalossof$20trillionin2015dollarestimates.Inthisperspective,althoughtheHighInflationWorldScenarioinflictssevereeconomicloss,thecatastrophedoesnotpreventtherecoveryoftheglobaleconomyovertime.
HighInflationasaFinancialCrisis
Scenarioselection
Inflationistiedtotherelationshipbetweenaggregatesupplyanddemand.Cost-pushdescribesasupplyshortage,e.g.,duetoadisruptioninproductionofacommodity.Demand-pulldescribesincreasingdemand,perhapsresultingfromalooseningofcredit.Inbothcases,inflationofcommoditypricesoccurs.TheHighInflationWorldScenarioisacost-pushsituationdrivenbyrelativescarcityofbothoilandagriculturalcommodities.Thefinalimpactofthesepricehikesdependsheavilyonthelevelofexposureacountryhastoeachcommodity.
1CambridgeCentreforRiskStudies,“ATaxonomyofThreatsforComplexRiskManagement”,2014
Nonetheless,thedirectimpactofaglobalhighinflationisthecorrespondingincreaseinunemploymentrates,albeitvaryingseverity,acrossmajoreconomies.
Variantsofthescenario
Wecalibratethreevariantsofthescenariousingdifferentlevelsofinflationforfoodandenergyprices.InourstandardscenarioS1,commoditypricesjumpbetween180and210%ofthepre-existingpricelevels,withpricespeakingaround15monthsaftertheinitialshock.ScenariovariantS2andextremevariantX1aresimilartothestandardscenario,butthecommoditypriceincreasesareraisedupto280and440%,respectively.
ThescaleoflossinflictedbytheHighInflationWorldScenariohasbeencalibratedtocorrespondapproximatelytoaneventthathappensaboutonceacenturyonaverage,a1-in-100yearevent.Twoindicatorsthatmaygiveasenseofthelikelihoodofacatastrophescenariooccurringareitsimpactonequityreturnsandgrowthrates,whichareexpectedtobenegativeasaresultofcatastrophe.
InthecaseoftheHighInflationWorldScenario,however,ouranalysisdoesnotshowextremebehaviourineitherofthesecategories.US(UK)equitiesoverthelasttwohundredyears2haveexperiencedreturnratesbelow-24%(-13%)aboutonceintwentyyears,withreturnratesbelow-36%(-20%)signifying1-in-100events.Inourscenariovariants,thosereturnratesarebarelyeffectedotherthanintheextremeX1variantinwhichequityreturnratesare-8%intheUSand-4%intheUK.
Nearzeroeconomicgrowthratesarefoundinourscenariosbutthesedon’tcomparetothehistoricalrecordforUS(UK)growthratesbeingbelow-7%(-3%),whichare1-in-20yearevents,orratesbelow-13%(-5%)whichhappenseverycentury.
2PriortorecordsfromFTSEandS&P,weusesurrogatestockssuchasthosefromAmericanrailroadstockpricesandotherconstructedindexes.Weusesimilarsurrogatedataforestimatinggrowthratespriortotheavailabilityofstandardiseddata.Ouridentificationof%ilesusesanormalcurvefittingwhichisconservativeinlightofthefattailsassociatedwithequitypricedistributions.
5
HighInflationWorldStressTestScenario
Thisisastresstest,notaprediction
ThisreportisoneofaseriesofstresstestscenariosthathavebeendevelopedbytheCentreforRiskStudiestoexploremanagementprocessesfordealingwithanextremeshock.Itdoesnotpredictacatastrophe.
Seedsofshortage
Farmingfailure
TheScenarioassumesthatthemiddleoftheyearbringswithitboutsofextremeweatheracrossthenorthernhemisphere:alongheatwaveinthePacificWest,floodsintheSub-Indiancontinent,heavyrainsintheAtlanticanddroughtinnorthernChina.Grainyieldsaresuretosuffer.
Concurrently,apandemicsweepsthroughtheworld’spopulationofbees.Inadequatepollinationpreventstheworldwidedevelopmentofnuts,fruitandotheragriculturalproducts.
HoldingtheStraitofHormuzHostage
AmilitantgroupestablishesholdontheStraitofHormuzinthePersianGulf,effectivelyseizingcontrolof20%oftheworld’scrudeexports.ThegrouprestrictstheinternationalshipmentofcrudeoilthroughtheStraits,hikingthepriceofoiltoover$170perbarrel.Theimpactaffectstheinternationalmeatanddairyindustriessignificantly.Thecombinationofhighproductioncostsandefficiencylossesaffectaggregatedemandasacost-pushspiralemergesworldwide.
Globalstagflation
Astheinternationalenergycrisiscontinuestheconsumerpriceindexspikesinmanynations,drivingdemandsfornationalwageincreases.Stagflationemergesacrosstheglobeascountriesthatimplementwagehikesexperienceanunemploymentspiral.
Inanefforttocurtailworldwidestagflationattheheightofthecrisis,nationalcentralbanksgraduallyadjustinterestratesinordertosuppressconsumerspendingandrelieveeconomicpressure.Aftereighteenmonths,pricesbegintostabiliseandtherateofinflationdrops.
GlobalGDPimpact
TounderstandhowtheHighInflationWorldscenarioimpactstheglobaleconomyweusetheGlobalEconomicModel(GEM),OxfordEconomics’quarterly-linkedinternationaleconometricmodel.Priceshocksareapplieddirectlytoworldfoodandenergypricesovera15monthperiod,andthemodeladjustsendogenouslytoallocateinflationrateincreasesacrosstheworld.
WeusetheGEMtoestimatethelossinglobalgrossdomesticproduct,cumulatedovera5yearperiod,whichisattributedtothisstresstestscenario.Wetermthisloss‘GDP@Risk’.
GPD@Risk,expressedinrealtermsinUSdollars,rangesfromalossof$US4.9trillionforS1to$US10.9trillionintheX1variant.
However,thisscenariodoesnotnecessarilyleadtoaglobalrecession,butinsteadslowsdowntheeconomicgrowthconsiderably.TheseimpactsaresignificantbutnotofthesamescaleastheGreatFinancialCrisis,from2008-2012,whoseGDP@Riskisaround$20trillionin2015dollars.
Financialmarketimpact
WeestimatetheportfolioimpactsofthisscenariobymodellingtheoutputsfromOEMintoportfolioreturns,projectingmarketchangesandcashflowswhilekeeptheallocationpercentagesfixed.Wealsodefaultallcorporatebondsgiventhe2008defaultrates.
Giventhattheconsumerpriceindex(CPI)wasdirectlyshockedinthemacroeconomicmodelling,weseethatthetotalportfolioreturnsinreal%aremoresignificantlyimpactedthaninnominaldollars.
ThemaximumdownturnexperiencedfortheConservativeportfoliointheS1variantis-3.89%innominalor-9.69%inrealtermsandoccursinYr2Q4.Bestandworstperformances(withinequities)aretheUK(FTSE100),andJapan(N225);withinfixedincome,USandJapanesebonds,withtheworstperformingportfoliostructurebeinghighfixedincome,at7.93%fortheS1variant.
ForportfolioprotectionitisrecommendedthatequityallocationisshiftedawayfromJapantowardsUKandawayfromJapanfixedincometowardsUSfixedincome.
Riskmanagementstrategies
Scenariosasstresstests
Thisscenarioisanillustrationoftherisksposedbysocialunresttriggeredbycatastrophicevent.TheHighInflationWorldscenarioisjustoneexampleofawiderangeofscenariosthatcouldoccur.
Thisscenarioaimstoimproveorganizations’operationalriskmanagementplansaroundcontingencies,andstrategiesforsurvivingfinancialandcounterpartychallenges.Itpresentsacapitalstresstestforinsurerstoassesstheirabilitytomanageunderwritinglosseswhilealsosufferingmarketimpactsontheirinvestmentportfolios.
6
CambridgeCentreforRiskStudies
SummaryofEffectsofHighInflationWorldScenarioandVariants
ScenarioVariantS1S2X1
VariantDescriptionStandardScenarioScenarioVariantExtremeVariant
Worldenergypriceshock210%280%440%
Worldfoodpriceshock180%250%310%
Pricespiralduration5Qtrs5Qtrs5Qtrs
Macroeconomiclosses
uiglobalGDP)1.9%1.4%0.6%
GlobalrecessiondurationNorecession
GDP@Risk$Tr
(5yearlossofglobaloutput)$4.9Trillion$8.0Trillion$10.9Trillion
i5s-rbaselineGDP)1.7%2.2%2.6%
PortfolioImpact
Performanceatperiodofmaxdownturn
HighFixedIncome-8%-10%-16%
Conservative-4%-7%-14%
Balanced-3%-6%-13%
Aggressive-1%-4%-12%
Assetclassperformance
Yr1Qr4Yr3Qr4Yr1Qr4Yr3Qr4Yr1Qr4Yr3Qr4
USEquities(W5000),%Change-20%4%-39%-36%-1%-1%
UKEquities(FTSE100),%Change-72%-43%-73%-49%-3%18%
USTreasuries2yrNotes,%Change0%3%0%5%-7%-16%
USTreasuries10yrNotes,%Change2%15%2%17%-13%-22%
Table1:SummaryimpactsoftheHighInflationWorldscenario
7
HighInflationWorldStressTestScenario
TrillionUS$GDP@Riskacrossscenarios
S1
S2
X1
1.6
4.6
8.1
MillennialUprising
SocialUnrestRisk
1.9
1.6
-1.6
DollarDeposed
De-AmericanizationoftheFinancialSystemRisk
15
4.5
7.4
SybilLogicBomb
CyberCatastropheRisk
HighInflationWorld
FoodandOilPriceSpiralRisk
4.9
8
10.9
10
23
7
SaoPaoloInfluenzaVirus
PandemicRisk
EurozoneMeltdown
SovereignDefaultRisk
11.2
16.3
23.2
GlobalPropertyCrash
AssetBubbleCollapseRisk
13.2
19.6
China-JapanConflict
GeopoliticalWarRisk
17
27
32
2007-12GreatFinancialCrisis
18
GreatFinancialCrisisat201420
Table2:GDP@RiskimpactoftheHighInflationWorldscenariocomparedwithpreviousCentreforRiskStudiesstresstestscenarios
8
CambridgeCentreforRiskStudies
2FinancialCatastropheStressTestScenarios
Thisscenarioisanillustrationoftherisksposedbyaplausiblebutextremefinancialmarketbasedcatastrophe.Itrepresentsjustoneexampleofsuchacatastropheandisnotaprediction.Itisa“what-if”exercise,designedtoprovideastresstestforriskmanagementpurposesbyinstitutionsandinvestorswishingtoassesshowtheirsystemswouldfareunderextremecircumstances.
ThisscenarioisoneofaseriesofstresstestscenariosdevelopedbytheCentreforRiskStudiestoexplorethemanagementprocessesfordealingwithanextremeshockevent.Itisoneoffourfinancialmarketcatastrophescenariosbeingmodelledunderthisworkpackageandincludesthefollowing:
.GlobalPropertyCrash:AssetBubbleCollapse;
.DollarDeposed:De-AmericanisationoftheGlobalFinancialSystem;
.EurozoneMeltdown:SovereignDefaultCrisis.
Thescenariospresentaframeworkforunderstandinghowglobaleconomicandfinancialcollapsewillimpactregions,sectorsandbusinessesthroughoutthenetworkedstructureoftheeconomy.Thesefinancialstresstestsaimtoimproveorganisations’operationalriskmanagementplanstoformcontingenciesandstrategiesforsurvivingandminimisingtheimpactsfrommarket-basedfinancialcatastrophe.
Inparticular,thestresstestsallowinstitutionstomanageandbuildresiliencetodifferentformsofriskduringperiodsoffinancialstress.
Theserisksinclude:
.financialandinvestmentriskstemmingfromacollapseinassetpricesacrossdifferentsectorsandregions;
.supplychainriskandtheabilityofaninstitutiontoeffectivelymanageitsinputrequirementsthroughitssupplychain,tomeetinternalproductionandoperationalrequirements;
.customerdemandriskandknowledgeforhowdemandmightshiftforgoodsandservicesduringperiodsoflowinvestmentandconsumerspending;
.marketorsegmentationriskandanunderstandingofhowotherfirmswithinthesamesectorwillreactandperformduringperiodsoffinancialstressandhowthismayimpactonthebusiness;
.reputationalriskandtheprotectionofbrandimageforreactingappropriatelyandconfidentlyundercrisisconditions.
Eachindividualscenariomayrevealsomeaspectsofpotentialvulnerabilityforanorganisation,buttheyareintendedtobeexploredasasuiteinordertoidentifywaysofimprovingoverallresiliencetounexpectedshocksthatarecomplexandhavemulti-facetedimpacts.
Marketcatastropheriskandfinancialcontagion
TheGreatFinancialCrisisof2007-8notonlyrevealedtheextenttowhichtheglobalfinancialsystemisinterconnectedbuthowinterrelationshipsbetweencommercialbanks,investmentbanks,centralbanks,corporations,governments,andhouseholdscanultimatelyleadtosystemicinstability.Asglobalfinancialsystemsbecomeincreasinglyinterconnected,ashocktoonepartofthesystemhasthepotentialtosendacascadeofdefaultsthroughouttheentirenetwork.
In2008,itwasonlythroughgovernmentinterventionintheformofextensivebailoutpackagesthatawidespreadcollapseoftheglobalfinancialsystemwasavoided.Newmodelsoftheglobalfinancialsystemareanessentialtoolforidentifyingandassessingpotentialrisksandvulnerabilitiesthatmayleadtoasystemicfinancialcrisis.
Theliteratureidentifiesthreetypesofsystemicrisk:(i)build-upofwide-spreadimbalances,(ii)exogenousaggregateshocksand(iii)contagion(Sarlin,2013).Similarlyweworkwiththreeanalyticalmethodsthathelpdealwithdecisionsupport:(i)early-warningsystems,(ii)macrostress-testing,and(iii)contagionmodels.AllthreemethodsareactivelyunderresearchintheCentreforRiskStudiesandutilisedinthedevelopmentofthesestresstestscenarios.
Understandingfinancialcatastrophethreats
Thisscenarioexplorestheconsequencesofafinancialmarketcatastrophebyexaminingthenotional1-in-100possibilityforaHighInflationWorldScenarioandexamininghowtheshockwouldworkthroughthesystem.
Foraprocessthattrulyassessesresiliencetomarketcatastrophe,weneedtoconsiderhowdifferentmarket-basedcatastrophesoccurandthenpropagatetheseshocksthroughglobalfinancialandeconomicsystems.Thisexercisewouldideallyincludeathoroughanalysisforeachdifferenttypeofmarketcatastropheinadditiontothefourfinancialcatastrophesincludedinthissuiteofstresstests.
9
HighInflationWorldStressTestScenario
Suchananalysiswouldalsoincludearangeofdifferentseveritiesandcharacteristicsforthesescenarioswouldoccurasaresultofthesedifferentfinancialandeconomiccrises.
TheCambridgeRiskFrameworkattemptstocategorizeallpotentialcausesoffutureshocksintoa“UniversalThreatTaxonomy.”Wehavereviewedmorethanathousandyearsofhistoryinordertoidentifythedifferentcausesofdisruptiveevents,collatingotherdisastercataloguesandcategorizationstructures,andresearchingscientificconjectureandcounterfactualhypotheses,combinedwithafinalreviewprocess.TheresultingCambridgetaxonomycataloguesthosemacro-catastrophethreatswiththepotentialtocausedamageanddisruptiontoamodernglobalisedworld.ThereportCambridgeSystemShockRiskFramework:Ataxonomyofthreatsformacro-catastropheriskmanagement(CCRS,2014)providesafulldescriptionofthemethodologyandtaxonomycontent.
Withinthisuniversalthreatframeworkwehavedevelopedaspecifiedtaxonomyforfinancialcatastrophes.ThiscanbeseeninFigure1andincludesalistofsevenuniquefinancial,marketandeconomiccatastrophes.Alargeeconomicorfinancialcatastropheseldomaffectsjustonepartofthesystem.
Thehistoricalrecordshowsthatmultiplemarketcatastrophestendtooccuratthesametimeandimpactscascadefromonecrisistothenext.TherecentGreatFinancialCrisis(GFC)isoneexampleofthis.ThefinancialcrisisstartedintheUSasasub-primeassetbubblebutquicklyspreadtothebankingsectorwheremanymajorbankswereleftholdingassetsworthmuchlessthanhadoriginallybeenestimated.Thecomplicatednatureofthevariousfinancialderivativesthatwerebeingsoldmadeitdifficultfortraderstounderstandthetrueunderlyingvalueoftheassetthatwasbeingpurchased.Thisresultwasasystemicbankingcollapsethathadworldwideimplicationsthatstillremainstobesolvedacrosstheglobe.
Throughouthistorytherehavebeenmanyotherexampleswheremultipleformsoffinancialcatastrophehavecascadedfromoneformofcrisistothenext,examplesincludethe1720SouthSeaBubble;1825LatinAmericanBankingCrisis;1873LongDepression;1893BearingBankCrisis;1929WallStreetCrashandDepression;1997AsianCrisisandthe2008GlobalFinancialCrisis.
Scenariodesign
Eachscenarioisselectedasaplausible,butnotprobable,extremeeventthatisdrivenbyanumberoffactorsandwouldcausesignificantdisruptiontonormallifestylesandbusinessactivities.
Theyareillustrativeofthetypeofdisruptionthatwouldoccurwithinaparticularcategoryof“threat”or“peril”–thatis,acauseofdisruption.
Inthisscenario,weexploretheconsequencesofa“HighInflationWorld”resultingfromafoodandenergypricespiral.Itisalsopossiblethatthatthisglobalphenomenoncouldhavebeentriggeredbyothercommoditypricespirals,notlimitedtojustfoodandenergy.
TheanalysisestimateslossestotherealeconomyusingtheOEMtocalculatelossesinexpectedGDPoutput.Wehavealsoestimatedhowtheeventwouldimpactinvestmentassetvalues,usingstandardizedinvestmentportfoliostoshowtheeffectonindicativeaggregatereturns.
Investmentmanagerscouldapplytheseassetvaluechangestotheirownportfoliostructurestoseehowthescenariowouldpotentiallyaffecttheirholdings.Theimpactsofthedifferentvariantsofthisscenarioareappliedtofourfinancialportfolios:highfixedincome,conservative,balancedandaggressive.
Developingacoherentscenario
Figure1:Financialcatastrophe“FinCat”taxonomy
Itisachallengetodevelopascenariothatisusefulforawiderangeofriskmanagementapplications.Fullyunderstandingtheconsequencesofascenarioofthistypeisproblematicbecauseofthecomplexityoftheinteractionsandsystemsthatitwillaffect.
Theeconomic,financial,andbusinesssystemsthatwearetryingtounderstandinthisprocessarelikelytobehaveinnon-intuitiveways,andexhibitsurprisingcharacteristics.
Duringthisprocesswetrytoobtaininsightsintotheinterlinkagesthroughusinganextremescenario.
Todevelopacoherentstresstestwehavedevisedamethodologyforunderstandingtheconsequencesofascenario,assummarisedinFigure2.
10
LossEstimation
Impactonworkforce;insurancelosslines;utilities;supplychains;finance;sentiment
MarketImpactAssessment
Valuationofkeyassetclasses,suchasequities,fixedincome,FX
CambridgeCentreforRiskStudies
Thisinvolvessequentialprocessingofthescenariothroughseveralstagesandsub-modellingexercises,withiterationprocessestoalignandimproveassumptions.
Webelieveitisimportanttocreatearobustandtransparentestimationprocess,andhavetriedtoachievethisthroughadetailedrecordingoftheassumptionsmade,andbymakinguseofsensitivitytestsregardingtherelativeimportanceofoneinputintoanother.
Inthemacroeconomicstagesofthemodelling,weareconsciousthatweareattemptingtopushmacroeconomicmodels,calibratedfromnormaleconomicbehaviour,outsidetheircomfortzone,andtousetheminmodellingextremeevents.Wehaveworkedcloselywitheconomiststounderstandtheusefullimitsofthesemodelsandtoidentifytheboundariesofthemodelsfunctionality.
ScenarioDefinition
Processdefinition,timeline,footprint,
sectoralimpacts,contagionmechanisms
MacroeconomicModelling
Sectoral®ionalproductivitylossonkeymetricssuchasGDP,Employment
Figure2:Structuralmodellingmethodologytodevelopacoherentstresstestscenario
Uncertaintyandprecision
Overallthescenarioconsequenceestimationprocessretainselementsofuncertainty.Theprocessentailsmakinganumberofassumptionstoassesslossesanddirectimpacts.Thesearethenusedasinputswithinamacroeconomicmodel,withadditionalassumptionsandtheintroductionofuncertaintyandvariation.
Theoutputsthenfeedtheassessmentofportfolioperformance,withfurtherassumptionsgeneratingadditionaluncertainty.Linkingallthecomponentsintoacoherentscenarioisproblematictoachieveandtheprocessdescribedinthisreportisoneparticularapproachthathasattemptedtodothis.
Itissuboptimalinthattheprocessisimpreciseandoneofcompoundeduncertaintyateachsuccessivestageandthemethodologyofvariousaspectsofanyparticularscenarioneedstobeunderstoodinthiscontext.
Thepoint,however,ofproducingthescenarioistounderstandtheconsequencesintermsoftheirholisticeffects,theirrelativeseveritiesandthepatternsofoutcomethatoccur.Infact,thescenarioisdeterministicandisnotdesignedtoprovideexceedanceprobabilitydatapoints.Anapproximationselectionprocesshasbeenadoptedonthebasisofexpertelicitation,tobeintherangeofthe1-in-100annualprobabilityofoccurrenceworldwide,butnotrigorouslydetermined.Thescenarioproductionprocess,limitedasitis,doesprovideinterestinginsights,andmanyoftheapplicationsofthescenarioareachievedthroughthisimperfectapproach.Thescenarioisofferedasastresstest,tochallengeassumptionsofcontinuingstatusquoandtoenablepractitionerstobenchmarktheirriskmanagementprocedures.
Useofthescenariobyinvestmentmanagers
Thescenarioprovidesatimelineandanestimationofthechangeoffundamentalvalueinassetsinaninvestmentportfolio.Thesearesegmentedintobroadassetclassesandgeographicalmarketstoprovideindicativedirectionalmovements.
Theseprovideinsightsforinvestmentmanagersintolikelymarketmovementsthatwouldoccurifaneventofthistypestartedtomanifest.Inrealevents,marketmovementscansometimesappearrandom.
Thisanalysis
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