剑桥风险研究中心-高通胀世界金融灾难压力测试（英）_市场营销策划_重点报告202301202_doc.docx

CentreforRiskStudiesp三UniversityofPCAMBRIDGEJudgeBusinessSchlCambridgeCentreforRiskStudiesUniversityofCambridgeJudgeBusinessSchoolTrumpingtonStreetCambridge,CB21AGUnitedKingdomries.riskj6s.cam.ac.ukhttp，WWW.risk.jbs.cam.ac.ukDecember2015TheCambridgeCentreforRiskStudiesacknowledgesthegeneroussupportprovidedforthisresearchbythefollowingorganisations:TheviewscontainedinthisreportareentirelythoseoftheresearchteamoftheCambridgeCentreforRiskStudies,anddonotimplyanyendorsementoftheseviewsbytheorganisationssupportingtheresearch.Thisreportdescribesahypotheticalscenariodevelopedasastresstestforriskmanagementpurposes.Itdoesnotconstituteaprediction.TheCambridgeCentreforRiskStudiesdevelopshypotheticalscenariosforuseinimprovingbusinessresiliencetoshocks.Thesearecontingencyscenariosusedfor*what-ifstudiesanddonotconstituteforecastsofwhatislikelytohappen.FoodandOilPriceSpiralStressTestScenarioHighInflationWorldContents1ExecutiveSummary42 DefiningtheScenario83 HighInflationasaFinancialCatastrophe124 DefiningtheScenario155 TheScenario176 MacroeconomicAnalysis197 ImpactonInvestmentPortfolio258 MitigationandConclusions329 Bibliography33FoodandOilPriceSpiralStressTestScenarioHighInflationWorld1ExecutiveSummaryInthefollowingreport,wepresentanarrativeofhowglobalinflationarypressureoverseveralyearsimpactstheworldeconomyandfinancialmarkets.Thisprovidesabasisforaglobalenterprisetotestitsoperationalandstrategicmodel,asasteptowardimprovingitsresilience.Scenariosmoregenerallycanbeusedtocoverthespectrumofextremeshocks,suchasthoseproposedintheCambridgeTaxonomyofThreats,whichencompassesfiveclassesofbusinessrisk.1HighInflationWorldScenarioThisscenarioemdsionscostshocksinresponsetoshrinkingglobaloilsuppliesand,simultaneously,disruptionstocropproductionthatleadtoglobalfoodshortages.Theseinflationarydriverspersistovermanymonths,causinginternationaleconomicandhumanitarianpressures.Theeconomicimpact,expressedaslostglobalGrossDomesticProductoverfiveyears,comparedwiththeprojectrateofgrowth("GDPRiSk")，isbetween$4.9,$8and$10.9trillion,dependingontheseverityofthecommoditypriceshock.TheGreatRecessionof2007-2011,comparatively,sawalossof$20trillionin2015dollarestimates.Inthisperspective,althoughtheHighInflationWorldScenarioinflictssevereeconomicloss,thecatastrophedoesnotpreventtherecoveryoftheglobaleconomyovertime.HighInflationasaFinancialCrisisScenarioselectionInflationistiedtotherelationshipbetweenaggregatesupplyanddemand.Cost-pushdescribesasupplyshortage,e.g.,duetoadisruptioninproductionofacommodity.Demand-pulldescribesincreasingdemand,perhapsresultingfromalooseningofcredit.Inbothcases,inflationofcommoditypricesoccurs.TheHighInflationWorldScenarioisacost-pushsituationdrivenbyrelativescarcityofbothoilandagriculturalcommodities.Thefinalimpactofthesepricehikesdependsheavilyonthelevelofexposureacountryhastoeachcommodity.,CambridgeCentreforRiskStudies,uATaxonomyofThreatsforComplexRiskManagement*,2014Nonetheless,thedirectimpactofaglobalhighinflationisthecorrespondingincreaseinUnemPlOymentrates,albeitvaryingseverity,acrossmajoreconomies.VariantsofthescenarioWecalibratethreevariantsofthescenariousingdifferentlevelsofinflationforfoodandenergyprices.InourstandardscenarioSi,commoditypricesjumpbetween180and210%ofthepre-existingpricelevels,withpricespeakingaround15monthsaftertheinitialshock.ScenariovariantS2andextremevariantXiaresimilartothestandardscenario,butthecommoditypriceincreasesareraisedupto280and440%,respectively.ThescaleoflossinflictedbytheHighInflationWorldScenariohasbeencalibratedtocorrespondapproximatelytoaneventthathappensaboutonceacenturyonaverage,a1-in-100yearevent.Twoindicatorsthatmaygiveasenseofthelikelihoodofacatastrophescenariooccurringareitsimpactonequityreturnsandgrowthrates,whichareexpectedtobenegativeasaresultofcatastrophe.InthecaseoftheHighInflationWorldScenario,however,ouranalysisdoesnotshowextremebehaviourineitherofthesecategories.US(UK)equitiesoverthelasttwohundredyears Prior to records from FTSE and S&P, We use surrogate stocks such as those from American railroad stock prices and other constructed indexes. We use similar surrogate data for estimating growth rates prior to the availability of standardised data. Our identification of%iles uses a normal curve fitting which is conservative in light of the fat tails associated with equity price distributions.haveexperiencedreturnratesbelow-24%(-13%)aboutonceintwentyyears,withreturnratesbelow-36%(-20%)signifying1-in-100events.Inourscenariovariants,thosereturnratesarebarelyeffectedotherthanintheextremeXivariantinwhichequityreturnratesare-8%intheUSand-4%intheUK.Nearzeroeconomicgrowthratesarefoundinourscenariosbutthesedon,tcomparetothehistoricalrecordforUS(UK)growthratesbeingbelow-7%(-3%),whichare1-in-20yearevents,orratesbelow-13%(-5%)whichhappenseverycentury.Thisisastresstest,notapredictionThisrep