紐約聯(lián)儲-經(jīng)銷商能力和美國國債市場功能

DealerCapacityandU.S.TreasuryMarketFunctionalityDarrellDuffie|MichaelFleming|FrankKeane|ClaireNelson|OrShachar|PeterVanTasselDealerCapacityandU.S.TreasuryMarketFunctionalityDarrellDuffieMichaelFlemingFrankKeane,ClaireNelson,OrShachar,andPeterVanTasselFederalReserveBankofNewYorkStaffReports,no.1070August2023/10.59576/sr.1070AbstractWeshowasignificantlossinU.S.Treasurymarketfunctionalitywhenintensiveuseofdealerbalancesheetsisneededtointermediatebondmarkets,asinMarch2020.AlthoughyieldvolatilityexplainsmostofthevariationinTreasurymarketliquidityovertime,whendealerbalancesheetutilizationreachessufficientlyhighlevelsliquidityismuchworsethanpredictedbyyieldvolatilityalone.Thisisconsistentwiththeexistenceofoccasionallybindingconstraintsontheintermediationcapacityofbondmarkets.JELclassificationG01,G1,G12,G18,E58Keywords:treasurymarket,liquidity,volatility,dealerintermediation,value-at-risk_________________FlemingKeaneShachar,VanTassel:FederalReserveBankofNewYork(emails:michael.fleming@,frank.keane@,or.shachar@,peter.vantassel@).Duffie:StanfordUniversity(email:duffie@).Nelson:PrincetonUniversity(email:cn7429@).TheauthorsthankIsabelKroghforresearchandDaronAcemogluWenxinDu,TerrenceHendershott,EdithHotchkiss,TifMacklem,AndrewMetrick,ZachModig,ImèneRahmouni-Rousseau,JeremyStein,JoshYounger,andtheparticipantsofWomeninMarketMicrostructure2023conferenceandBISAnnualMeetingResearchConferenceforcomments.TheyalsothankDamirFilipovi?,MarkusPelger,andYeYeforhelpwithaccessingtheirresultsonfittedTreasurydiscounts.ThismaterialisbaseduponworksupportedbytheNationalScienceFoundationGraduateResearchFellowshipProgramunderGrantNo.DGE-2039656.Thispaperpresentspreliminaryfindingsandisbeingdistributedtoeconomistsandotherinterestedreaderssolelytostimulatediscussionandelicitcomments.TheviewsexpressedinthispaperarethoseoftheauthorsanddonotnecessarilyreflectthepositionoftheFederalReserveBankofNewYorkortheFederalReserveSystem.Anyerrorsoromissionsaretheresponsibilityoftheauthor(s)anddonotnecessarilyreflecttheviewsoftheNationalScienceFoundation.Toviewtheauthorsdisclosurestatementsvisit/research/staff_reports/sr1070.html.11IntroductiononeThisisconsistentwiththeexistenceofetntto1Forexample,seeDuffie(2020);Goldberg(2020);Brainard(2021)andHe,Nagel,andSong(2022).2SeeGroupofThirty(2021,2022)andUSDepartmentoftheTreasury,BoardofGovernorsoftheFederalReserveSystem,FederalReserveBankofNewYork,USSecuritiesandExchangeCommission,andUSCommodityFuturesTradingCommission(2021,2022).3SeeComerton-Fordeetal.(2010);Adrianetal.(2013);Bessembinderetal.(2018);Duffie(2020);Gold-berg(2020);BreckenfelderandIvashina(2021);Fontaineetal.(2021)andHe,Nagel,andSong(2022).3aingeflowsisproxiedbytheratioUit=Xit/XofthecurrentlevelXitofthatintermediation4measuretoitscorrespondingmaximumX=max{Xi1,...,XiT}overtheTdaysintheedis對iwiUit,where對iX.wi=對iX.nD4SeeAppendixTableD.10,whichshowsthecross-sectionalvariationofdealercapacityutilizationmea-sures,onpeakdaysandacrosstheentiresample.5ResultsforeachofthethreematuritysectorsaresimilarandreportedinAppendixTableD.5.5Figure2.Dealercapacityutilizationmeasures.Dealercapacityutilizationmeasuresbasedonrisk-adjustedgrosspositions,netpositions,grossdealer-to-customer(D2C)volume,andnetD2Cvolume.Averagecapacityutilizationisthesimpleaverageofthefourmeasures.ety6Figure3.USTreasurymarketilliquidityandyieldvolatility.Treasuryilliquidityisthefirstprincipalcomponentofsixilliquiditymeasuresacross2-,5-,and10-yearmaturitysectorsasshowninFigure1.Yieldvolatilityistheaveragevolatilityimpliedbyswaptionswithone-monthexpirationson2-,5-,and10-yearinterest-rateswaps.Theseriesareplottedasfive-daymovingaveragesofz-scores.Thesamplecorrelationoftheunderlyingtwodailytime-seriesis89%.ens7Figure4.RelationshipbetweenUSTreasurymarketilliquidityandyieldvolatility.Ascatterplotandestimatedrelationshipbetweentheprincipal-componentcompositemeasureofTreasuryilliquidityandacompositemeasureofimpliedvolatility,asmeasuredbytheaverageofthestandarddeviationsofbenchmarkswaprates,inbasispoints,impliedbyswaptionson2-,5-,and10-yearswapswithone-monthexpirations.Theplottedordinary-least-squaresfit,forJuly10,2017toDecember31,2022(T=1,336),isthesecond-orderpolynomialy=?1.81+0.026x+0.000005x2,wherevolatilityxisinbasispoints,R2=79.5%.Theconstantandlinearcoefficientestimateshavep-valuesoflessthan1%understandardassumptions.tlof8Figure5.RelationshipbetweenUSTreasurymarketilliquiditynotexplainedbyyieldvolatil-ityandaveragedealercapacityutilization.Ascatterplotoftheresidualilliquiditythatremainsaftercontrollingforaverageswaption-impliedvolatility(theresidualsassociatedwiththefittedrelationshipinFigure4)andaveragedealercapacityutilization.Theaveragecapacityutilizationistheaverageofthedealercapacityutilizationmeasuresbasedondealergrosspositions,dealernetpositions,grossdealer-to-customervolume,andnetdealer-to-customervolume.Theplottedordinary-least-squaresfit,forJuly10,2017toDecember31,2022,isthesecond-orderpolynomialy=0.363?0.048x+0.0013x2,withR2=43.6%.Allthreecoefficientestimateshavep-valuesoflessthan1%usingNewey-Weststandarderrors.9enPnLdata.ooflhet2Relationtopriorworkondealerliquidityprovisionet6IntheprimarymarketforreverseauctionsofUKgilts,Boneva,Kastl,andZikes(2020)findthatdealerssellgiltsmoreaggressivelywhentheyhaveunwantedinventory,orwhentheytookadditionalgiltpositionsjustbeforethereverseauctions,orwhentheyaremoreconstrainedbytheleverage-ratiorule.7See,forexample,Adrian,Etula,andMuir(2014);Etula(2009);He,Kelly,andManela(2017);HeandKrishnamurthy(2012);He,Nagel,andSong(2022);BaronandMuir(2022);Du,Hebert,andLi(2022);Fleming,Rosenberg,andNguyen(2022);KlinglerandSundaresan(2023);Boyarchenkoetal.(2018);Jermann(2020);FinancialStabilityBoard(2020);He,Khorrami,andSong(2022);HeandKrishnamurthy(2018).ingeoss8Theymodelthecosttodealersofusingbalancesheetspaceasη(q+VaR),whereqisdealerinventoryandthecostcoefficientηisaninputparameter.Huangetal.(2023)assumethatVaRisproportionaltothevarianceofpositionvalue,q2σ2,whereσ2isthevarianceoftheassetprice.Themarginalcostofbalancesheetusageisthenη+2ησ2q.Inpractice,VaRisdefinedinawaythatisroughlyproportionaltothestandarddeviationofthepositionvalue,qσ.Withthat,thecostofliquidityprovisioninthesenseofHuangetal.(2023)wouldbeoftheformpS=η(1+σ),whichdoesnotdependonthepositionsizeq.Empirically,wefindthatatanylevelofdealercapacityutilization,illiquidityrisesatarelativelyconstantratewithvolatility,whereasbalance-sheetutilizationplaysaclearadditionalroleonlywhenitreachesasufficientlyhighlevel.ls3LiquidityprovisionintheUSTreasurymarketDCyeeofradayn9SeeUSDepartmentoftheTreasury,BoardofGovernorsoftheFederalReserveSystem,FederalRe-serveBankofNewYork,USSecuritiesandExchangeCommission,andUSCommodityFuturesTradingCommission(2015).atTRACEdataforontherunandofftherundegtsscusipy10ThefullreportingrequirementareavailableatFINRA’swebsite.esecurities.Tothatend,weuseTRACEdataforagencyMBSandcorporatebondstosyonssnnd5Liquiditymetricschegeomls11ForourJuly10,2017toDecember31,2022sampleperiod,wefindaverageyieldcurvenoiseof1.7basispointsusingtradedpricesversus1.2basispointsusingindicativeclosingquotesfromCRSPdata.AveragesforMarch2020are3.3and2basispoints,respectively.12BrokerTecisourdatasourceforrepurchaseagreement(“repo”)specials’ratesandvolumes.Figure6.LoadingsonfirstprincipalcomponentofUSTreasurymarketilliquiditymeasures.Loadingsfor18individualmetricscomprisedofsixliquiditymeasurestimesthreematurities.6DealercapacityutilizationRdQ=對iQDV01itVolitQ=|對iQDV01itVolit|Q=對i(對=0Q)DV01itVolitQ=|對i(對=0Q)DV01itVolit|,qdt∈{Q,Qt,Q,QtD2C},veutilizationMtdwdfdtusingcapacityweightswdmddmdthatareproportionaltoineAsillustratedinSection1,inaperiodofstressedsellingsuchasMarch2020,theUS13SeeKoenkerandHallock(2001)forbackgroundonquantileregressionmodeling.llty14Onecanrecovertheestimateddependenceofthequantileofilliquidityontheun-residualizedmeasureofdealercapacityutilizationbyexploitingthelinearityofboththeOLSandquantilemodels.Suppose,foreacht∈{1,...,T},thatxt=A\ztforxtandztinRnandsomefixednonsingularn×nmatrixA.Supposefurtherthatb*=argminb對tf(b\zt)forsomef:R→R.Thenargminc工f(c\xt)=argminc工f(c\A\zt)=A?1b*.ttAppendixD.6appliesthisresulttoourquantileregressionsetting.Itreportsthefirststageregressionsofcapacityutilizationontovolatilityfromwhichtheimpliedcoefficientscanbederivedalongwithquantileregressionsusingun-residualizedcapacityutilizationforcomparison.h15Pseudo-R2isdefinedas對tρτ(yt?xβ)/對tρτ(yt?y?τ)wherey?τistheunconditionalτ-thquantileandρτ(u)=ρτ=u·(τ?1u<0)isthepiece-wiselinearquantilelossfunction.16Giventhepersistenceofthedependentandexplanatoryvariables,weuseblockbootstrappedstandarderrorsfollowing(Gregory,Lahiri,andNordman,2018)tomeasuresignificance.InunreportedresultsweUnivariate:b:Bivariate:b:c:Bivariate:dealercapacity-utilizationresidualsFigure7.USTreasurymarketilliquidityconditionaldistributionslopecoefficientsbyper-centilebasedonvolatilityanddealercapacityutilizationmeasuredbasedonrisk-adjustedgrosspositions.PlotstherelationshipbetweenTreasuryilliquidity,volatility,andresidualizedcapacityutilizationfromquantileregressions.Panel(a)reportstheslopecoefficientsfromunivariatequantilere-gressionswithvolatilityfordifferentpercentiles.Theordinary-least-squares(OLS)coefficientisreportedasasolidbluelinewiththedashedlinesindicatinga95%confidenceinterval.IfhigherlevelsofvolatilityresultedinasimplelocationshiftinthedistributionofilliquiditywewouldexpectsimilarcoefficientsacrossquantilestotheOLScoefficient.Panels(b)and(c)reporttheslopecoefficientsonvolatilityandthecapacityutilizationresidualfrombivariatequantileregressionsfordifferentpercentiles.Grosspositioncapacityistherisk-adjustedutilization,andresidualizedrelativetovolatility.Theexplanatoryvariablesarestandardizedtomaketheslopecoefficientscomparable.offindsimilarlevelsofsignificanceandstandarderrorsusingasemiparametricbootstrapprocedurefollowingEfronandTibshirani(1994)thatisdescribedinAppendixD.717Inourmainresults,weaggregatethenetmeasuresofdealercapacityutilizationusingtheabsolutevalueofthenettradevolumeornetpositionscaledbyitshistoricalmaximum.Thenetmeasuresthusidentifywhendealershavelargeimbalancesrelativetotheirhistoricalnetpositions,irrespectiveofthesignofthenetpositionorofthecorrelationofnetpositionsacrossdealers.Ifdealersarelessconnectedduringperiodsofmarketstress,aggregatingdealerlevelnetmeasuresinthismannermaybeappropriateforhighlightingtimeswhendealershavelargeimbalancesorabsolutenetpositionsrelativetotheirwithin-dealerhistoricallevels.Wealsoconsideredaspecificationinwhichweaggregatethesignednetpositionacrossdealersandthencomputetheabsolutevalueafteraggregating.Ifdealershaveoffsettingnetpositionsorflows,thisalternativespecificationofthenetmeasurewillbelowerthanourbaselinemeasurewhichlooksattheimbalanceorabsolutenetmeasurewithindealer.Inunreportedresultswefoundthatthisalternativedefinitionresultedinsimilarstatisticalsignificanceandexplanatorypowerofnetpositions.DefiningnetD2Cpurchasevolumesinthisalternativewayresultsinapositiveslopecoefficientbuttherelationshipisnolongersignificant.Table1:Quantileregressionsfor99thpercentileofUSTreasurymarketilliquidity.Reportsquantileregressionsforthe99thpercentileofTreasuryilliquidityontovolatilityandcapacityutilization.Foreaseofinterpretationallvariablesarestandardizedintheregressions.Standarderrorsareblockbootstrappedwithablocksizeof100daysfollowingthesmooth-extendedtaperedapproachfromGregory,Lahiri,andNordman(2018).(1)(2)(3)(4)(5)Yieldvolatility2.16***(0.48)1.06***(0.14)1.12***(0.14)1.25***(0.16)1.14***(0.12)Capacityutilizationresidual:grossposition0.57***(0.17)Capacityutilizationresidual:netposition0.43**(0.17)Capacityutilizationresidual:grossD2Cvolume0.51***(0.17)Capacityutilizationresidual:netD2Cvolume0.41**(0.16)Constant1.80***(0.50)1.01***(0.15)0.97***(0.15)1.16***(0.21)0.91***(0.13)NPseudoR20.540.740.740.710.74***p<0.01,**p<0.05,*p<0.1sonrrFigure8.HeatmapofUSTreasurymarketilliquidity.PlotsthefittedvalueforTreasuryilliquiditygiventhelevelofvolatilityandresidualcapacityutilizationforthe50th,75th,95th,and99thpercentilesoftheconditionaldistributionfromquantileregressions.Volatilityismeasuredastheaverageone-monthimpliedvolatilityon2-,5-,and10-yearswaps.Capacityutilizationismeasuredwithdealergrosspositions.Theresidualofcapacityutilizationcapturesthecomponentnotexplainedbyvolatility.Eachofthevariablesisstandardized.Therangeofthevariablesisdeterminedbythehistoricalminimumandmaximumduringoursampleperiod.zona8IlliquidityandVaRcapacityutilizationing18TheMRRdataiscollectedpursuanttoBaselIIISubpartF(MarketRisk)Section205asdescribedhere.TheMRRappliestoBoard-regulatedinstitutionswithaggregatetradingassetsandliabilitiesequalto$1billionormoreorthatareequalto10%ormoreofquarter-endtotalassetsasreportedonthemostrecentquarterlyCallReport(FRY-9C).TheMRRdataincludesadailymeasureofVaRforeachsubportfoliocalibratedtoaone-tail,99.0percentconfidencelevelandthedailyPnLofthesubportfoliobasedonthenetchangeinthepriceofthepositionsheldasoftheendofthepreviousbusinessday,excludinganycommissions,fees,orbid-askspreadsthataregeneratedbynewpositions.for19Dealersmustincludemultipliersandadd-onfactorsintheirrequiredregulatorycapitalwhenPnLexceedsreportedVaRthresholds.Abboudetal.(2021)describesalargenumberofPnL“exceptions”duringMarchgTable2:QuantileregressionsfordealercapacityutilizationmeasuredwithdealerValue-at-Risk.Reportsquantileregressionsforthe99thpercentileofUSTreasurymarketilliquidityontoyieldvolatilityandcapacityutilization.Capacityutilizationismeasuredwithvalue-at-risk(VaR)atthebankholdingcompany(BHC)levelandfordeskswithexposuretointerestraterisk(IR).VaRisaone-day99-percentilemeasurethatisreportedbythedealerasrequiredbytheMarketRiskRuleorthatisestimatedfromdailyprofit-and-lossdata.Foreaseofinterpretationallvariablesarestandardizedintheregressions.Standarderrorsareblockbootstrapped.(1)(2)(3)(4)(5)Yieldvolatility2.16***(0.47)2.11***(0.47)2.20***(0.52)1.32***(0.23)1.26***(0.16)Capacityutilizationresidual:BHCVaRDealer0.26*(0.15)Capacityutilizationresidual:IRVaRDealer0.25*(0.14)Capacityutilizationresidual:BHCVaREstimated0.52***(0.17)Capacityutilizationresidual:IRVaREstimated0.44***(0.17)Constant1.80***(0.50)1.51***(0.40)1.61***(0.45)0.96***(0.21)0.85***(0.13)NPseudoR20.540.600.570.720.75***p<0.01,**p<0.05,*p<0.1ionsfirymarketgiventherapidgrowthinerin20See,forexample,Duffie(2020);Logan(2020);LiangandParkinson(2020);Busettoetal.(2022);Flemingetal.(2022).21SeeUSDepartmentoftheTreasury,BoardofGovernorsoftheFederalReserveSystem,FederalRe-serveBankofNewYork,USSecuritiesandExchangeCommission,andUSCommodityFuturesTradingCommission(2021,2022).SeealsoGroupofThirty(2021,2022).22See"SECProposesRulestoImproveRiskManagementinClearanceandSettlementandtoFacilitateAdditionalCentralClearingfortheUSTreasuryMarket,"pressrelease,September14.eeyAbboud,A.,C.Anderson,A.Game,D.Iercosan,H.Inanoglu,andD.LynchAdrian,T.,N.Boyarchenko,andO.Shachar(2017):“DealerBalanceSheetsandAdrian,T.,E.Etula,andT.Muir(2014):“Financialintermediariesandthecross-Adrian,T.,M.Fleming,J.Goldberg,M.Lewis,F.M.Natalucci,andJ.J.WuAdrian,T.,M.Fleming,O.Shachar,andE.Vogt(2017):“MarketliquidityafterAdrian,T.,M.Fleming,andE.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mtyBAdditionaldetailsaboutthedataB.1TreasuryTRACEincludeallmarketableTreasuries,includingbills,notes,bonds,TIPS,andFRNs.TheheudedB.2IdentifyingprimarydealersinTreasuryTRACEerthe syB.3FR2004granularityceCAdditionaldetailsabouttheilliquiditymeasuresC.1On-the-runinterdealermeasuresre2-yearticksizechange,andouradjustmentUSTreasurysecuritiesarequotedandYi,t=αi+γt+βPosti×Treatmentsi+εi,t(1)whereYitiseitherbidaskspreadorthenegativelogdepthTreatmentisanindicatorlTableC.1:Effectsofticksizereductiononspreadsanddepths.Reportstheresultsofthedifferences-in-differencesregressioninEquation(6)estimatedforthe2-,5-,and10-yearnotesfromSeptember24,2018throughJanuary11,2019.tstatisticsinparentheses.?p<.1,??p<.05,???p<.01(1)(2)NegativelogdepthPosttick-sizechange*1[2-Year]EsTerm,tradingdateTerm,tradingdateNi,t=Yi,t?β(2)FigureC.1.Tick-sizeadjustmentfor2-yearspreadanddepth.Time-seriesplotofadjustedandunadjusted2-yearproportionalspreadsandnegativelogdepthforJanuary2,2017throughDecember30,C.2Off-the-runD2CmeasuresldnYieldcurverootmeansquareerror(RMSE)FollowingHu,Pan,andWang(2013),cestoe23Themedianamountoftimebetweenthetradeandquoteislessthan2secondsfortheoff-the-runinstitutionalD2Ctradesinoursample.Werequirethateachtradehaveaquoteforthesamesecuritywithinatleastonehourbeforethetradetobeincludedinthesample.Wewinsorizethetrade-leveldispersionmeasureat25basispointsinyieldspacetomitigatetheimpactofoutliers.Thisismeanttobeaconservativefilterinthatforoursampleoftrades,the99thpercentileis8.5basispoints.eTableC.2:SummarystatisticsfordifferencebetweenCRSPandTradewebquotesThistablereportssummarystatisticsforthedifferencebetweenCRSPquotesandaverageTradewebquotesoverdiffer-entend-of-dayintervalswhenavailable.Thesampleincludestheissue-daysunderlyingourRMSEmeasurebasedonTRACED2Ctradesfortheoff-the-runmarket.Wecomputethedifferencebetweentheend-of-daymid-quotesanddividebytheDV01oftheissuetoexpressthedifferenceinbasispointsofyield-to-maturity.PanelA:CRSPminusTradewebaverage4:55pmto5:00pman2yOFR5yO