原油现货和期货价格关系协整线性和非线性因果关系外文翻译.docx

原油现货和期货价格关系协整线性和非线性因果关系外文翻译.docx

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原油现货和期货价格关系协整线性和非线性因果关系外文翻译

外文题目：

TheRelationshipbetweenCrudeOilSpotandFuturesPrices:

Cointegration,LinearandNonlinearCausality

出处：

EnergyEconomics

作者：

SteliosD.Bekiros,CeesG.HDiks

原文:

TheRelationshipbetweenCrudeOilSpotandFuturesPrices:

Cointegration,LinearandNonlinearCausality!

Abstract

Thepresentstudyinvestigatesthelinearandnonlinearcausallinkagesbetweendailyspotandfuturespricesformaturitiesofone,two,threeandfourmonthsofWestTexasIntermediate（WTI）crudeoil.ThedatacovertwoperiodsOctober1991-October1999andNovember1999-October2007,withthelatterbeingsignificantlymoreturbulent.ApartfromtheconventionallinearGrangertestweapplyanewnonparametrictestfornonlinearcausalitybyDiksandPanchenkoaftercontrollingforcointegration.Inadditiontothetraditionalpairwiseanalysis,wetestforcausalitywhilecorrectingfortheeffectsoftheothervariables.Tocheckifanyoftheobservedcausalityisstrictlynonlinearinnature,wealsoexaminethenonlinearcausalrelationshipsofVECMfilteredresiduals.Finally,weinvestigatethehypothesisofnonlinearnon-causalityaftercontrollingforconditionalheteroskedasticityinthedatausingaGARCH-BEKKmodel.WhilstthelinearcausalrelationshipsdisappearafterVECMcointegrationfiltering,nonlinearcausallinkagesinsomecasespersistevenafterGARCHfilteringinbothperiods.Thisindicatesthatspotandfuturesreturnsmayexhibitasymmetriesandstatisticallysignificanthigher-ordermoments.Moreover,theresultsimplythatifnonlineareffectsareaccountedfor,neithermarketleadsorlagstheotherconsistently,videlicetthepatternofleadsandlagschangesovertime.

Keywords:

Nonparametricnonlinearcausality;OilFuturesMarket;Cointegration;

Theroleoffuturesmarketsinprovidinganefficientpricediscoverymechanismhasbeenanareaofextensiveempiricalresearch.SeveralstudieshavedealtwiththeLead-lagrelationshipsbetweenspotandfuturespricesofcommoditieswiththeobjectiveofinvestigatingtheissueofmarketefficiency.GarbadeandSilber（1983）firstpresentedamodeltoexaminethepricediscoveryroleoffuturespricesandtheeffectofarbitrageonpricechangesinspotandfuturesmarketsofcommodities.TheGarbade-SilbermodelwasappliedtothefeedercattlemarketbyOellermannetal.（1989）andtothelivehogcommoditymarketbySchroederandGoodwin（1991）,whileasimilarstudybySilvapulleandMoosa（1999）examinedtheoilmarket.BoppandSitzer（1987）testedthehypothesisthatfuturespricesaregoodpredictorsofspotpricesintheheatingoilmarket,whileSerletisandBanack（1990）andChenandLin（2004）testedformarketefficiencyusingcointegrationanalysis.CrowderandHamed（1993）andSadorsky（2000）alsousedcointegrationtotestthesimpleefficiencyhypothesisandthearbitrageconditionforcrudeoilfutures.Finally,SchwarzandSzakmary（1994）examinedthepricediscoveryprocessinthemarketsofcrudeandheatingoil.

Intheory,sincebothfuturesandspotprices“refect”thesameaggregatevalueoftheunderlyingassetandconsideringthatinstantaneousarbitrageispossible,futuresshouldneitherleadnorlagthespotprice.However,theempiricalevidenceisdiverse,althoughthemajorityofstudiesindicatethatfuturesinfluencespotpricesbutnotviceversa.Theusualrationalizationofthisresultisthatthefuturespricesrespondtonewinformationmorequicklythanspotprices,duetolowertransactioncostsandflexibilityofshortselling.Withreferencetotheoilmarket,ifnewinformationindicatesthatoilpricesarelikelytorise,perhapsbecauseofanOPECdecisiontorestrictproduction,oranimminentharshwinter,aspeculatorhasthechoiceofeitherbuyingcrudeoilfuturesorspot.Whilstspotpurchasesrequiremoreinitialoutlayandmaytakelongertoimplement,futurestransactionscanbeimplementedimmediatelybyspeculatorswithoutaninterestinthephysicalcommodityperseandwithlittleup-frontcash.Moreover,hedgerswhoareinterestedforthephysicalcommodityandhavestorageconstraintswillbuyfuturescontracts.Therefore,bothhedgersandspeculatorswillreacttothenewinformationbypreferringfuturesratherthanspottransactions.Spotpriceswillreactwithalagbecausespottransactionscannotbeexecutedsoquickly（SilvapulleandMoosa,1999）.Furthermore,thepricediscoverymechanism,asillustratedbyGarbadeandSilber（1983）,supportsthehypothesisthatfuturespricesleadspotprices.Theirstudyofsevencommoditymarketsindicatedthat,althoughfuturesmarketsleadspotmarkets,thelatterdonotjustechotheformer.Futurestradingcanalsofacilitatetheallocationofproductionandconsumptionovertime,particularlybyprovidingamarketschemeininventoryholdings（Houthakker,1992）.Inthiscase,iffuturespricesforlatedeliveriesareabovethoseforearlyones,delayofconsumptionbecomesattractiveandchangesinfuturespricesresultinsubsequentchangesinspotprices.AccordingtoNewberry（1992）futuresmarketsprovideopportunitiesformarketmanipulationbythebetterinformedorlargerattheexpenseofothermarketparticipants.Forexample,itisprofitablefortheOPECtointerveneinthefuturesmarkettoinfluencetheproductiondecisionsofitscompetitorsinthespotmarket.Finally,supportforthehypothesisthatcausalityrunsfromfuturestospotpricescanalsobefoundinthemodelofdeterminationoffuturespricesproposedbyMoosaandAl-Loughani（1995）.Intheirmodelthefuturespriceisdeterminedbyarbitrageurswhosedemanddependsonthedifferencebetweenthearbitrageandactualfuturespriceandbyspeculatorswhosedemandforfuturescontractsdependsonthedifferencebetweentheexpectedspotandtheactualfuturesprice.Thereferencepointinbothcasesisthefuturespriceandnotthespotprice（SilvapulleandMoosa,1999）.

Theaimofthepresentstudyistotestfortheexistenceoflinearandnonlineacausallead-lagrelationshipsbetweenspotandfuturespricesofWestTexasIntermediate（WTI）crudeoil,whichisusedasanindicatorofworldoilpricesandistheunderlyingcommodityofNewYorkMercantileExchange's（NYMEX）oilfuturescontracts.Weapplyathree-stepempiricalframeworkforexaminingdynamicrelationshipsbetweenspotandfuturesprices.First,weexplorenonlinearandlineardynamiclinkagesapplyingthenonparametricDiks-Panchenkocausalitytest,andaftercontrollingforcointegration,aparametriclinearGrangercausalitytest.Inthesecondstep,afterfilteringthereturnseriesusingtheproperlyspecifiedVARorVECMmodel,theseriesofresidualsareexaminedbythenonparametricDiks-Panchenkocausalitytest.InadditiontoapplyingtheusualbivariateVARorVECMmodeltoeachpairoftimeseries,wealsoconsiderresidualsofafullfive-variatemodeltoaccountforthepossibleeffectoftheothervariables.Thisstepensuresthatanyremainingcausalityisstrictlynonlinearinnature,astheVARorVECMmodelhasalreadypurgedtheresidualsoflineardependence.Finally,inthelaststep,weinvestigatethenullhypothesisofnonlinearnon-causalityaftercontrollingforconditionalheteroskedasticityinthedatausingaGARCH-BEKKmodel,againbothinabivariateandinafive-variaterepresentation.Ourapproachincorporatestheentirevariance-covariancestructureofthespotandfuturepricesinterrelationship.TheempiricalmethodologyemployedwiththemultivariateGARCH-BEKKmodelcannotonlyhelptounderstandtheshort-runmovements,butalsoexplicitlycapturethevolatilitypersistencemechanism.Improvedknowledgeofthedirectionandnatureofcausalityandinterdependencebetweenthespotandfuturesmarkets,andconsequentlythedegreeoftheirintegration,willexpandtheinformationsetavailabletopolicymakers,internationalportfoliomanagersandmultinationalcorporationsfordecision-making.

Theremainderofthepaperisorganizedasfollows.Section2brieflyreviewsthelinearGrangercausalityframeworkandprovidesadescriptionoftheDiks-PanchenkononparametrictestfornonlinearGrangercausality.Section3describesthedatausedandSection4presentstheresults.Section5concludeswithasummaryandsuggestionsforfutureresearch.

Figure1displaysthespotandfuturepriceandreturnstimeseries.Thefollowingnotationisused:

“WTISpot”isthespotpriceand“WTIF1”，“WTIF2”，“WTIF3”and“WTIF4”arethefuturespricesformaturitiesofone,two,threeandfourmonthsrespectively.DescriptivestatisticsforWTIspotandfutureslog-dailyreturnsarereportedinTable1.Specifically,thereturnsaredefinedas

wherePtistheclosingpriceondayt.ThedifferencesbetweenthetwoperiodsarequiteevidentinTable1whereasignificantincreaseinvariancecanbeobservedaswellasahigherdispersionofthereturnsdistributioninPeriodIIreflectedinthelowerkurtosis.Additionally,PeriodIIwitnessedmanyoccasionalnegativespikesasitcanbealsoinferredfromtheskewness.TheresultsfromtestingnonstationarityarepresentedinTable2.

Specifically,Table2reportstheAugmentedDickey-Fuller（ADF）testforthelogarithmiclevelsandlog-dailyreturns.ThelaglengthswhichareconsistentlyzeroinallcaseswereselectedusingtheSchwartzInformationCriterion（SIC）.Allthevariablesappeartobenonstationaryinlog-levelsandstationaryinlog-returnsbasedonthereportedp-values.Table1alsoreportsthecorrelationmatrixatlag0（contemporaneouscorrelation）forbothperiods.Significantsamplecross-correlationsarenotedforspotandfuturesreturnsindicatingahighinterrelationshipbetweenthetwomarkets.However,sincelinearcorrel