161208 Methods for evaluation of the Nordic forward market for electricity · 2016-12-12 ·...

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MethodsforevaluationoftheNordicforwardmarketforelectricityANALYSESINACCORDANCEWITHTHEFCAGL

Client: NVEincooperationwithEI,EVandDERAContact: CathrineHoltedahlDate: 8December2016Responsible: JørgenBjørndalen,ECGroupASTeam: OlvarBergland OlleBjörk BjörnHagman PetrSpodniak

MethodsforevaluationoftheNordicforwardmarketforelectricity —2—

Contents

Summaryandconclusions................................................................................................................3 1 Introduction...............................................................................................................................5 2 Acceptablerisklevelsatacceptablecosts–hedgingstrategiesinpractice..............................7

2.1 Theoreticalperspectivestohedging..........................................................................7 2.2 Objectivesforhedgingstrategies..............................................................................9 2.3 HedgingstrategiesintheNordicelectricitymarket................................................11 2.4 Jetfuelhedgingstrategiesintheaviationindustry.................................................14 2.5 Hedgingstrategiesinthealuminiumindustry.........................................................24 2.6 Conclusions..............................................................................................................26

3 Measuringrelevanceofhedgeinstruments............................................................................27 3.1 Thecorrelationanalysisdependsonthehedgingstrategy.....................................27 3.2 Correlationanalysisinpractice................................................................................30 3.3 Summaryofsuggestedmethod...............................................................................36

4 Evaluationofcontractefficiency.............................................................................................38 4.1 Backgroundonliquidity,efficiencyandpowerderivativespricing.........................40 4.2 Descriptivemeasures...............................................................................................41 4.3 Pricemeasures.........................................................................................................44 4.4 Transactioncostmeasures......................................................................................53 4.5 Summaryofsuggestedefficiencymeasures............................................................56

5 Bibliography.............................................................................................................................57

Summaryandconclusions

TheupcomingassessmentsoftheNordicelectricitymarketbytheregulatorscanberegardedasmirroringtheassessmentsmadebymarketparticipantswhenthesearedevelopingandpursuingtheirhedgingstrategies.Akeydifferencethough,betweentheFCAGLandrealhedgingstrategiesisthatmarketparticipantsareconcernedaboutallrisks,notjustpricerisks.Keyfeaturesofhedgingstrategiesinseveralsectorsarethattheyarepragmaticandinformal.

• Pragmaticmeansthatriskmanagementisatoolandnotagoalperse.Companiestendtomaximiseprofitswithinconstraints,andrisksareonegroupofconstraints.Thechallengeisthereforetofindtheacceptablelevelofriskforacceptablecosts.Therearenumerousexamplesofpotentialhedgesthatarenotused–simplybecausethecostsareconsideredtoohigh.‘Costs’hereincludesbothanapparentlyhighriskpremiuminacontract,thatthehedgemayreducenegativerisksbutatthesametimeforecloseattractiveprofitopportunities,andtheinternaladministrativecostsofmanagingacomplexhedgeportfolio.

• Pragmaticalsomeansthatwhenexecutingthehedgingstrategies,riskcommitteesarecommonlyinvolved.Thisreflectsthatmarketparticipantsoftendonothaveclearthresholdsorlimitsdictatingwhattodo.Afrequentfeatureofhedgingstrategiesisthatcompaniestendtoapplysomesortofmarketview.Thismeansthathedgingdecisionsmaybedependenton(internal)priceprognoses.

• Pragmaticfurthermeansthatmanycompanieswanttoavoidfluctuatingquarterandannualresultsbecauseoffluctuationsinthemark-to-marketvalueoftheirhedges.ItisimportantforthemthattheirauditorsapprovethattheirhedgesarequalifiedforhedgeaccountingaccordingtoIAS39.Therefore,thechoiceofusingproxiesornotmainlydependsontheirauditor’sviewonthecorrelationbetweentheproxyandthehedgeditem.

• Informalmeansthatthehedgingismostoftennotbasedonformalcorrelationormarketanalysis.

• Informalpartlyreflectstheinvolvementofriskcommitteesetc.,butalsothatanalysesiftheyaredonetendtobeadhocortailormade,andnotperformedatfixedorregularintervals.

Theoryandexperiencesshowthatcompleteeliminationofriskisnotoptimal,butratherthathedgingafractionoftheportfolioeitherdirectlyorindirectlythroughproxiesyieldthe“highestpay-off”tothehedger.Amean-varianceapproachtohedginghasanimportantimplicationfortheassessmentofhedgingopportunitiesintheelectricitymarket.Usingastandardmean-varianceanalysisthecompositionandperformanceofselectedportfolioswithsystempriceandEPADscanbeanalysedandevaluated.

Fortheanalysisofcorrelation,wesuggesttheregulatorscompareyearlyandmonthlyaveragezonalpriceswithsimilaraveragesoftheunderlyingforpotentialhedginginstruments,suchasSYScontracts,EPADsfortheactualbiddingzoneorEPADsforotherbiddingzones,andareacontractsforadjacentbiddingzoneslikeGermany,oracombinationofsuch.Amethodicalchallengeisthatthereisessentiallyaninfinitenumberofpotentiallyrelevantcombinations.Thepurposeoftheanalysesmustbetotestwhetherthepricesinthedeliveryperiodarewellcorrelatedornot,andnottoexaminethechangesinthevalueofthehedgingportfolioandthehedgeditemduringthehedgingperiod.Hence,theapproachtakeninthehedgeaccountingliteratureisnotrelevantformeasuringcorrelationintheregulators’assessments.

Fortheanalysisofefficiency,wesuggestthreegroupsofanalyses.Allanalysesrelyondirectmarketdatawithouttheneedforestimating,modellingorforecastingcomplexsystems,whichinitselfwouldbearuncertainty.

• Descriptivemeasures:Wesuggestthatanalysesoftradedvolumesandopeninterestarecoupledwithinformationoftradinghorizons.Theanalysesshouldprovideinsightintradingactivitypercontract(year,month,etc.)andperlocation.Dataarereadilyavailable,andtherequiredcomputationaleffortislimited.Thedescriptivemeasurescanbecomparedwithdescriptivemeasuresregardinglong-termtransmissionrights.

• Pricemeasure:Wesuggestcalculatingtheex-postriskpremiumseparatelyforyearandmonthcontracts,basedonacomparisonofthelastclosingpricebeforethecontractsgotodeliveryandtheactualdeliveryprices.Riskpremiumsshouldbeanalysedforasufficientlongperiodoftime,perhapsfiveyears.Theapproachwillyieldinsightonthemarketdynamicsbetweenbuyersandsellersofderivatives.Byobservingmagnitudes,directions,andsignificanceofex-postriskpremiumsacrosstradinghorizonsandbiddingareas,possiblesystematicbiasesinthepricingofderivativescanbeidentified.

• Transactioncostmeasure:Bestbid-askspreadsobtainedeitherfromexchangesorOTCbrokerswillanswerquestionsonthecostofhedgingaswellastheunderlyingliquidity.Themagnitudesofthequotedbid-askspreadswillrevealthetransactioncostsmarketparticipantsfacewhenparticipatinginthepowerderivativesmarkets.

Unfortunately,therearenoidentifiedthresholdsforthevariousmeasures.Thereisnoquickfixforthis,andthusaseparateobjectivefortheanalysesmustbetogainexperiencewiththeperformanceofthefinancialmarket.

Whenpreparingafinalconclusion,notethatthereisatrade-offbetweengoodcorrelationandlowtransactioncosts.Whenbuildingupahedgeportfolio,Itcanbebettertoacceptimperfectcorrelationifthealternativecontractsaremoreliquidand/oraretradedwithlowerriskpremiumsandtransactioncosts.

Lackoftradeinsomecontractsmightbeacompletelyrationalsolutionforanefficientmarket.Operatingmarketsarenotcostless;thereareonlyalimitednumberofeconomicallyjustifiablefuturesmarkets.

1 Introduction

On26September2016theEuropeanCommissionadopteditsregulation(EU)2016/1719establishingaguidelineonforwardcapacityallocation(FCA).Theregulationenteredintoforce17October2016.

TheFCAGLrequiresfortwokindsofdecisionsthattheregulatorsassesswhethertheelectricityforwardmarketprovidessufficienthedgingopportunitiesintheconcernedbiddingzones(Article30(3).Thefirstdecisionisnottoissuelong-termtransmissionrights(LTTRs)onabiddingzoneborder(Article30(1).TheseconddecisionisregardingintroductionofLTTRsifLTTRsdonotexistonabiddingzoneborder(Article30(2).Theassessmentshallincludeatleastaconsultationwiththemarketparticipantsabouttheirneeds,acorrelationanalysisandananalysisofwhetherproductsofferedareefficient.FCAGLleavesittotheregulatorstodecidethedetailsofthemethodsforsuchanalyses.

TheNordicenergyregulatorsarecommittedtocarryoutsuchanassessment,whichshallidentifywhethertheelectricityforwardmarketprovidessufficienthedgingopportunitiesintheconcernedbiddingzones.Topreparetheassessment,theNorwegianWaterResourcesandEnergyDirectorate(NVE)incooperationwiththeSwedishEnergyMarketInspectorate(Energimarknadsinspektionen),theFinnishEnergyAuthority(Energiavirasto),andtheDanishEnergyRegulatoryAuthority(DERA)commissionedthisstudy.Thetaskforthisstudyhasbeentoevaluatedifferentcriteria/indicatorsrelevantfortheassessmentofhedgingopportunitiesintheNordicelectricitymarketandtoprovideinsightofhedgingactivitiesfromother,comparablesectors(mainlycommoditymarkets).Theobjectiveforthestudywastopresentajustifiedsuggestiononthespecificmethod/stobeusedbytheregulatorsintheirevaluationofthefinancialelectricitymarketsasrequiredintheFCAGL.Whilethisreportthuspresentsproposalsformethods,therearenoattemptstoassessthehedgingopportunitiesindifferentpartsoftheNordicelectricitymarket.

OneofthescopesfortheFCAGListoensurethatmarketparticipantshavesufficienthedgingopportunitiesforelectricitypricerisks.Thetworelevantkeytermsinthisrespectaresufficientcorrelationandefficienthedginginstruments,neitherofwhicharepreciselydefinedintheregulation.Thecorrelationissuedealswiththemarketparticipants’challengetoidentifyforwardcontract(s)thatcanbeusedtohedgepricevolatility,andtoanalyseifsuggestedcontractsaresuitableforhedgingthepricerisk.Theefficiencyissueaddressestheconcernformarketparticipantsthatthehedgemaybetoocostly.Themostimportantfactorsareliquidity,relativesizeofriskpremiumsand(other)transactioncosts.

Ourstartingpointforthisstudyisthattheassessmentstheregulatorsareabouttodo,correspondtowhat(rational)marketparticipantsdowhendevelopingtheirhedgingpolicies/risk

managementstrategies.Inthissense,theregulators’assessmentmirrorthemarketparticipants’analyses–exceptthattheregulatorstoalargerdegreemustbeabletopresenttheirmethodsexplicitly.WenotethatwhiletheFCAGLfocusesonhedgingofpricerisks,marketparticipantshaveabroaderperspectiveandobjectivefortheirhedgingstrategies.

Ourapproachhasthusbeentoexaminethemethodsandproceduresactuallyappliedbymarketparticipants,basedonourownandothers’practicalexperiencefromvariousmarkets,andcombinethiswithrelevantacademicliterature.Itisclearthatthemarketparticipants’methodsarelessformalandexplicitthantheregulatorsmayhavewishedfor.Furthermore,therearegenerallynoformal(andexternal)requirementstothemarketparticipants’assessments.

Thereportthusfollowsthesamestructure:First,wepresentmarketparticipants’hedgingstrategiesandmethods.Theirobjectivecangenerallybedescribedasreducingriskstoacceptablelevels(sufficientcorrelation)atacceptablecosts(efficientproducts).Wecontinueinchapter3byexploringhowcorrelationanalysisshouldbestructuredproperlytoreflectthechallengesfacedbymarketparticipants,andproceedinchapter4withmethodstoevaluatecontractefficiency.Thereisarichacademicliteratureaboutmeasuringefficiency,particularlyinfinancialandcommoditymarkets(stocks,grains,etc.).Applicationsinelectricitymarketsarelessfrequent,andourapproachhasbeentofocusonmethodsthatreflectsmarketparticipants’perspectiveswhilelimitourselvestomethodsthathavebeenappliedinanalysesofelectricitymarketsandthatarenottoocomputationallycomplex.

2 Acceptablerisklevelsatacceptablecosts–hedgingstrategiesinpractice

Inthischapterwewillexploredifferentfeaturesofhedgingstrategiesindifferentindustries.Theaimistoprovidearealisticbackgroundforanalysesofwhethercurrentmarketsprovidesufficienthedgingopportunitiestoelectricitymarketparticipants.Westartwithashortandgeneraldescriptionofhedgingpurposes,andendwithacloserlookoncurrenthedgingstrategiesinvariousindustries.

TheFCAGLrequirestheregulatorstoassesswhethertheelectricityforwardmarketprovidessufficienthedgingopportunitiesintheconcernedbiddingzones.Theassessmentshallincludeatleastaconsultationwiththemarketparticipantsabouttheirneeds,acorrelationanalysisandananalysisofwhetherproductsofferedareefficient.TheFCAGLleavesittotheregulatorstodecidethedetailsofthemethodsforsuchanalyses.

Withinaccounting,thereisalreadysome‘globalrules’foranalysesofforwardmarkets,wherepracticehasdevelopedintogenerallyacceptedstandardsforhowtoperformcorrelationanalysesandhowtoevaluatetheresultsofthevarioustests.Akeyquestionisifsomeoftheseaccountingstandardsaretransferrabletotheregulators’tasks.Therearesomeclearparallelsinthescopeoftheseanalyses,andpreviousdiscussionsinitiatedbytheNordicregulatorshavealsoraisedtheissueexplicitly.Wehavethereforeinsertedasectiondiscussingtherelevanceoftheseglobalaccountingstandards.

Acommonfeatureofallmarketsisthatperfecthedgesonlyexistsintextbooksandtheoreticalexamples.Evenifthereisperfectcorrelationbetweentheunderlyingofafinancialcontractandthepriceofactualdeliveries,theefficiencyofhedgesrelyingonthatparticularcontractislikelytobelessperfectduetovolumevariations.Marketparticipantsaregenerallyfacedwithamixedchallenge;theymustconsidertheappropriatenessofavailablefinancialpricesaswellastheimpactfromothertypesofrisk;volumerisk,legalrisk,operationalrisk,regulatoryrisk,etc.

2.1 Theoreticalperspectivestohedging

Futuresmarketsforagriculturalcommoditieshavebeeninoperationformorethanahundredyears,andagriculturalcommoditiesdominatedfuturesmarketsforalongtime.Thereisavastliteratureonthefunctioningofagriculturalfuturesmarkets,theirroleforpricediscoveryandasariskmanagementtool.Thepurposeofthissectionistogiveanoverviewofsomeoftheseissuesastheypertaintohedging(andtheirrelevanceforforwardelectricitymarkets).

Thetraditionalhedgingtheoryemphasizestheriskavoidancepotentialoffuturesmarkets(Alexander,2008).Thefuturesmarketsareviewedasamechanismthroughwhichpriceriskcanbetransferredfromonesetofagentstoanother.Keynes(1936)setforthhistheoryofnormalbackwardationinwhichthehedgersarewillingtopayariskpremiumtoreducetheirpricerisk,whilethespeculatorsarewillingtoenterthefuturesmarketonlyiftheexpecttocollectapremium.ThehypothesisofbackwardationhasbeensubjecttoextensivetestingstartingwithTelser(1958)refutationinhisstudyofwheatandcottonmarkets.Thisconclusionhasbeenmainlybeenmaintainedintheliterature(Fama&French,1988;Carter,1999).Furthermore,thetraditionalviewholdsthatthepurposeofhedgingistoremoveallriskfromthehedgingportfolio(Alexander,2008).

ThetraditionalviewofhedgingasinsurancewaschallengedbyWorking(1953b,a)whoarguedthatthehedgerdoesnotseekprimarilytoavoidriskbutonewhohedgesbecauseofanexpectedreturnfromthetradingactivity.ThemeanvarianceviewofhedgingwasintroducedbyJohnson(1960)andStein(1961),andextendedtoproducersbyMcKinnon(1967)andAndersonandDanthine(1983).Inthisapproach,hedgingistheprocessofsimultaneouslychoosingfuturespositionsandcashpositionsinordertoconstructaportfolioofassets(Carter,1999;Alexander,2008).Thehedgerisassumedtomaximizetheexpectedvalueofherutilityfunctiononthebasisoftheirmeansandvariances,e.g.usingamean-varianceobjectivefunction.Thismean-varianceapproachtoagriculturalriskmanagement,includinghedging,hasbeenincorporatedintotextbookssincethe1970s(Anderson,Dillon,&Hardaker,1977;Tomek,1972).

Portfoliohedginghasbeenextendedtoproxyhedgingwheretherearenoforwardorfuturesmarketsforsomecommodities(Ederington,1979;Alexander,2008).Furthermore,thelocationalbasisriskhasbeenexploredforanumberofcommoditiesandlocations(Carter,1999).Anearly,andtypical,studybyBobst(1973)concludedthathedgingisaseffectiveinareaswithoutdeliverypointsasinareaswithdelivery.Hearguedthatthecontinuedeffectivenessofthehedgingopportunitydependsuponliquidityinthefuturesmarketandstablespatialpricepatterns.

Themean-varianceandportfolioapproachtohedgingshowsthatcompleteeliminationofriskisnotoptimal,butratherthathedgingafractionoftheportfolioeitherdirectlyorindirectlythroughproxiesyieldthe“highestpay-off”tothehedger(Ederington,1979;WilliamsJ.,1986).Themean-varianceapproachalsohasanimportantimplicationfortheassessmentofhedgingopportunitiesintheelectricitymarket.Usingastandardmean-varianceanalysis(Alexander,2008)thecompositionandperformanceofselectedportfolioswithsystempriceandEPADscanbeanalysedandevaluated.

Thenumberofactiveorganizedfuturesmarketsissmallcomparedtothepotentialnumberofcommodities,grades,locationsandfutureperiods.Manyseethelackoffuturesmarketsasafailureofthemarketsystemitself(Arrow,1978).However,asoperatingmarketsarenotcostlessthereareonlyalimitednumberofeconomicallyjustifiablefuturesmarkets(WilliamsJ.,1986).

Thenumberofeconomicallyjustifiablemarketsiswherethemarginalbenefitsofamarketequalsthemarginalcostsofoperatingsaidmarket.

2.2 Objectivesforhedgingstrategies

Theprimaryobjectiveformarketparticipantsisnormallytomaximiseprofits,typicallywithinconstraintsrelatedtofactorslikeriskexposure,amongotherthings.Thisleadstoanobjectiveforriskmanagement,ingeneralterms,toreduceriskstoacceptablelevelsatacceptablecosts.Thishastwoimplications:

1. Thereisgenerallynopointineliminatingallrisksandaimfortheperfecthedge–investorsexpecttheircompaniestotakesome(specific)risks,andcustomerspayaccordingly.Ifallrisksarehedged,thereisinasensenobusinessbecausethenyoursuppliersand/orcustomerscandoyourjobbetterthanyoudoityourself.

2. Thecostofhedgingmatters.Thusiftheavailablehedges(orsomeextrahedges)aretoocostly,meaningthatacceptingthemeliminatesallprofitopportunities,thequestionisessentiallyifyoucanacceptoperatingwithoutsuchhedges.Iftheunhedgedrisksareunacceptable,themarketparticipanthasnofutureintheindustry.

Hence,formostmarketparticipantstheobjectiveofhedgingistohavesomeoneelsetoabsorbthoserisksthattheycannotorwillnotabsorbthemselves.Thehedgingstrategymustensurethattheexposurestocrucialrisksarewithinacceptablelimits,setbytheownerand/orthemanagement.

Notethatregardingthecostofhedging,theremightbetwoalternativeexplanationsifahedgeappearsascostly.Iftheriskishigh,thecostofinsuranceisalsohigher,ascomparedwithasituationwithlowrisk.Itsimplymightbecostlytoofferthehedge.Forelectricitycontracts,thismeansthatthepropertiesoftheprobabilitydistributionsforelectricitypricestoalargeextentdeterminethehedgingcosts.Themorevolatiletheday-aheadpricesare,thecostlieritwouldbeforsomeonetoguaranteeafixedpriceinsteadofthevolatileday-aheadprice.Alternatively,(orinaddition),theinsurancemarketmightbeinefficient.If,forinstance,thereisonlyonesupplierofinsurance,thechancesarehighthatthepriceforinsuranceisalsohigh.Itcanbehardtodistinguishbetweenthesetwopossibleexplanations,butitisobviousthattotheextentthecauseofcostlyhedgingisrelatedmarketbehaviourandmarketdesign,itisworthwhiletoconsidermeasurestoimprovethesituation.

Further,hedgingretailing,whichisalowmarginbusiness,ishardlycomparabletohedginggeneration,whichishighriskandpotentiallyhighrewardbusiness.Retailersofferingfixedpricecontracts(orcontractswherepricescannotbeadjustedeasilyonashortnotice)wanttohedge

theirsalestoend-usersinordertoreduceormanagetheirpricerisk.Generatorsaretypicallymoreeagertosecuresomeoftheirexpectedprofitsforward.Industrialcustomershaveanothersituation.Electricitycanbeanimportantpartoftheircostsbuttheirmainbusinessistheproductstheyproduceandsell.Thusdifferentmarketparticipantshavedifferentrequirementsforhedging.

Notealsothatwhatmattersformarketparticipantsisnotonlythepricerisk,whichisthekeyissueinthisreport,butthetotalimpactofvolatileprices,uncertaintiesregardingvolumes(supplyand/ordemand),aswellasnumerousrisksanduncertaintiesrelatedtootherfactors(legalrisks,counterpartyrisks,operationalrisks,etc.).Thefactthatthefinancialsituationofthemarketparticipantalsoimpactsthedemandforhedging,addscomplexitytothispicture.

InternationalFinancialReportingStandards(IFRS)aredesignedasacommongloballanguageforbusinessaffairssothatcompanyaccountsareunderstandableandcomparableacrossinternationalboundaries.TheEuropeanUniondecidedin2002thatfrom2005IFRSwouldapplyfortheconsolidatedaccountsoftheEUlistedcompanies.IFRSaretherulestobefollowedbyaccountantstomaintainbooksofaccountswhicharecomparable,understandable,reliableandrelevantforinternationalusers.Thisobjectiveisratherdifferentfromobjectivesforhedgingstrategiesamongmarketparticipantsintheelectricitysector.

OneofthekeyprinciplesinIFRSisthatderivativessuchaspowerderivativesshouldbebookedatmark-to-marketvalue.Changesofthemark-to-marketvaluebetweenperiodsshouldhaveimmediateeffectontheprofitandlossaccount(P&L).IAS39(IASisshortforInternationalAccountingStandards)providesanexemptionfromthisruleforqualifiedhedgingportfolios.Theexternalauditormayaccepthedgeaccountingifthecompanycandemonstrateaclosecorrelationbetweenthevalueofahedgingportfolioandthevalueofahedgeditem.Ifchangesinbotharewellcorrelated,hedgeaccountingcanbe’granted’.Companiesseekingacceptanceforhedgeaccountingmustthereforepresentacorrelationanalysis,andsubscribetoarather‘mechanical’hedgingstrategy(explainedfurtherbelow).

Manycompanieswithlistedstocksorbondsconsiderhedgeaccountingasimportantandprefertoavoidexplainingvolatilityofresultsduetochangesinthemark-to-marketvaluationoftheirhedgingportfolios.Theoriginalobjectiveforhedgingpowercostswasinfactformanyindustrialuserstoavoidvolatilityofresultsbecauseofvolatilityofpowercosts.Ifthepreferredhedgingstrategybysuchacompanyisnotacceptedforhedgeaccountingbyitsauditors,thecompanychoosesoftenbetweenendingitsuseofpowerderivativesortoadaptitshedginginsuchawaythathedgeaccountingisacceptedbytheauditor.

Thesituationisdifferentforacompanywithelectricityasitsmainbusiness.Suchacompanywillinanycasehavetoexplaintothestockmarkethowthevolatilityintheelectricitymarketaffectsitsresults.Also,thefinancialanalystsfollowingthecompanyareoftenwell-informedabouttheelectricitymarket.Suchacompanycanperceivemorefreedomofactiontonotperformhedge

accountingifitspreferredhedgingstrategyisnotacceptedbyitsauditors.Industrialconsumerswithonlyafewmainownerscanalsoperceivemorefreedomofaction.Ifthemanagementcancommunicatethebenefitstothemainowners,possibleover-reactionsinthestockmarketarenotsodeterrent.

Art.30(4)oftheFCAGLfocusesonpricerisks,whereasboththehedgeaccountingrulesandnormalhedgingstrategiesfocusonrisks.‘Risks’areclearlyamuchbroadertermthanpricerisk.If,forinstance,thehedgecontractisanelectricitybaseloadfuturescontract,andthehedgeditemisapowerplantwithutilisationtimearound4000hours,thecorrelationbetweenthevalueofthehedgecontractandthehedgeditemmaybeweakevenifthehedgecontracthastherelevantlocalpricesasitsunderlying.Ifthisarrangementdoesnotpasstheauditor’scorrelationtests,theauditormaynotallowhedgeaccounting.Theproblemisthennotthatthecorrelationofpricesisinsufficient(itmayinfactbeperfect),butthatthevolumeisdifferentinthecontractandforthepowerplant.

Thetermmechanicalhedgingstrategyreferstoahedgingstrategynotdependingone.g.thecurrentpricelevel.Thealternativeisadynamichedgingstrategy,andimpliesthathedgesarenotexecutedunlesstheresponsibledecisionmakeriscomfortablewiththepricelevelofthehedgecontracts.Adynamichedgingstrategycouldalsomeanthatthehedgeportfolioisreversedintheeventofbeneficialpricemovementsandre-establishedwhenpriceshave‘settled’atamorecomfortablelevel.Amechanicalstrategydoesnotallowforsuchflexibility,buthastobeexecutedatpredefinedintervalsorevents.

2.3 HedgingstrategiesintheNordicelectricitymarket

Traditionally(i.e.beforere-regulationstartedinthe1990s),bilateralphysicalcontractswereusedforbuyingandsellingelectricity.Fixed-pricecontractsprotectedcustomersfromtheriskofincreasingpriceswhereasgeneratorswereprotectedfromtheriskofreducedprices.Retailsaleswereoftenanintegratedpartofthebusinessforgenerators.Therewasalsophysicaltradebetweengeneratorsonacase-by-casebasis.Acquisitionofcross-bordercapacitieswereaprerequisiteforcross-bordertrades.Inseveraljurisdictions,utilitiesalsoenjoyedmonopolyrightsthateffectivelyprotectedthemfrompricerisksandothertypesofrisks.

Theriseoforganisedday-aheadmarketsinthe1990shasopenedupopportunitiesforotherbuyingandsellingstrategies.Consumersandretailerscanbuytheirelectricityintheday-aheadmarketandgeneratorscansellelectricityinthesamemarket.Physicaltradingintheday-aheadmarketinsteadofbilateralphysicalcontractsfacilitatescompetitiononequaltermsandcostreductionsformostparticipantssinceallparticipantsintheday-aheadmarketmeetthesamepriceirrespectiveoftheirsize.Thedrawbackisthatvolatileday-aheadpricesleadtosubstantialpricerisks.Long-termcontractscanbeusedforhedgingofsuchrisks.

NordPoolwasestablishedin1993asanorganisedday-aheadmarketforNorway.BrokersstartedquicklytodevelopastandardisedcontractforOTCtrading.ThepointofdeliverywasnormallySmestad(thetransformeroutsideStatnett’sheadofficeinOsloatthetime),andcontractsweresettledphysically.However,moreandmoremarketparticipantsfoundthatphysicaldeliveryatSmestadwasn’tconvenient.Thephysicalsettlementmeantheavyadministrativeburdensforcompanieswithportfoliosofseveralhundredsofcontracts.AnotherproblemwasthatNorwaywasdividedinseveralbiddingzonesandchangesinthebiddingzonesoccurredfrequently.

ContractswithaNorwegiansystempriceasthereferencepricethereforebecamemorepopularandNordPoolstartedtolistsuchcontracts.TheNorwegiansystempricewascalculatedbyNordPoolintheday-aheadmarketauctionasthepricethatwouldhavebeentheclearingpriceiftherewerenocongestionsbetweentheNorwegianbiddingzones.

NordPoolwastransformedtoaNorwegian-Swedishpowerexchangein1996whenSwedenreformeditselectricitymarket.FinlandjoinedNordPoolin1998,WesternDenmarkin1999andEasternDenmarkin2000.ThesystempriceasthereferencepriceforfinancialcontractshasgraduallybeenexpandedfromaNorwegiansystempricetoaNorwegian-Swedishsystemprice,toaNorwegian-Swedish-FinnishsystempriceandfinallytoaNordicsystemprice.

Thusfortwentyyears,hedgingofthebasicpriceriskshasbeenconcentratedaroundsystempricecontracts.Theliquidityinthemarketforsystempricecontractsgrewveryfastuntil2002.Manynon-NordiccompaniesjoinedNordPoolandstartedextensivetrading.ThevolumeinclearedNordicfinancialcontractswasover3000TWhin2002.Togetherwiththevolumeintheday-aheadmarket,thiscorrespondedtoachurnrateof9.ThecollapsesofEnronandTXUEuropeledtoanexodusofmostUSpowercompaniesfromEuropein2003.ThevolumeinclearedNordiccontractsdroppedtounder2000TWhin2003.

Systempricecontractsarebaseloadcontractsfordays,weeks,months,quartersandyears.Figuresfortradingactivityandopeninterestsinthedifferentmaturitiesindicatethatvolumevariationswithinaweekarenormallyignoredinthehedgingportfolios.Volumevariationswithinlongertimeframesareusuallyhedgedbybuildingaportfolioofcontractsfordifferentperiods,e.g.largerhedgevolumesduringwinterthansummer.

ThesystempricecanbeinterpretedasapriceforavirtualNordiczone,butitisnotbyanymeansapriceforaphysicalpointofdelivery.Physicaldeliveriesaresettledagainstthepriceforaspecificbiddingzone.Theconsequenceisaremainingriskforadifferencebetweenthesystempriceusedforbasichedgingandthephysicalbiddingzoneprice.Marketparticipants,inparticularretailersandconsumersinSweden,FinlandandDenmark,wantedapossibilitytoalsohedgethedifferencebetweenthelocalbiddingzonepriceandthesystemprice.CfDs(laterEPADs)werethereforeintroducedin2000.AnEPAD(ElectricityPriceAreaDifferential)isa

financialcontracttohedgetheaveragedifferencebetweenabiddingzonepriceandtheNordicsystemprice.EPADsareavailableasbaseloadcontractsformonths,quartersandyears.

Thedifferencesbetweenzonalpricesandthesystempricearelessvolatilethanthesystempriceitselfifmeasuredinabsoluteterms(EUR/MWh).Changesinpricesandpriceexpectationsthattriggerchangingthecontentofthehedgingportfoliosresultnormallyinbuyingorsellingsystempricecontracts,whiletheportfoliosofEPADsarekeptmorestable.

EPADcontractsarenamedafteramajorcitywithintherelevantbiddingzone,sothatÅrhuscorrespondstoDK1,CopenhagentoDK2,HelsinkitoFinland,LuleåtoSE1,SundsvalltoSE2,StockholmtoSE3,MalmötoSE4,OslotoNO1andTromsøtoNO4.Currently,therearemarketmakersforthetwoDanishareas,thefourSwedishareasandforFinland(aswellasforLatvianandGermanEPADs).

TherearenoEPADcontractslistedfortheNorwegianbiddingzonesNO2,NO3andNO5andthereislittlerequestforsuchcontractsfromretailersandindustrialconsumers.OnereasonisthataveragedifferencesbetweenthesystempriceandNorwegianareapricesaresmallerthanthedifferencesbetweenthesystempriceandDanish,FinnishorSwedishareaprices.ThisreflectsthatNorwegianhydroproductionhasnormallyhighshort-termflexibility.ThesystempriceisthereforemostoftenneartoNorwegianareaprices.

TheoverallfeedbackinstudiesoftheNordicmarketisthatnoneofinterviewedmarketparticipantswanttoreplacethebasichedginginsystempricecontractswithbasichedgingindifferentareapricecontracts.Thecombinedliquidityinsystempricecontractsisseenasessentialandtheyfearfragmentedliquidityiftherearedifferentareapricecontracts.Marketactorsinallpriceareasbenefitfromthehighliquidityinthefinancialcontractslinkedtothesystemprice.

Interviewswithmarketparticipants,forthisprojectandforpreviousprojects,revealthathedgeaccountingiscommonamongindustrialcustomers.ButmanyNordicelectricitygeneratorsandretailersdonotbothertoobtainhedgeaccounting.Generally,theycaneasilyexplainrevenuevolatilitycausedbyahedgingstrategytotheirstakeholders.However,auditorsmaystilldemandthatthecompaniespursuerathermechanicalhedgingstrategies,withlimitedflexibilitytoadapttomarketviews.Thishastheinterestingconsequencethatlowliquidityofthehedginginstrumentisnotnecessarilyanissue–oncethehedgeisestablishedasashortorlongpositioninaspecificcontract,themechanicalstrategyrequiresthecompanytokeepthecontractandletitgotodelivery.

InterviewsalsoconfirmthatthebasisforanyNordichedgingportfolioisacarefullyexaminedpositioninSYScontracts.TheroleoftheSYSpartoftheportfolioistoprovideprotectionfromthemajorpricemovementsthattendtoaffectallmarketareas.Forthereminderofthepricerisks,twokindsofanalysesareapplied–similartothelogicoftheFCAGLart.30.IfanEPADexist

fortherelevantbiddingzone,thereisonesetofanalysestoconsidertheperformanceofsaidEPAD:costofhedging,riskpremiumandliquidity.IftherelevantEPADisconsiderednotgoodenough,asecondsetofanalysesisappliedtodetermineifalternativeEPADsorthesystempricealonehavesufficientcorrelationwiththerelevantzonalprice.

Theapproachinthecorrelationanalysesvariesamongmarketparticipants.SomeseemtofollowanapproachconsistentwithwhatauditorsrequirewhenconsideringhedgeaccountingandIAS39,whileothersevaluatecorrelationmorealongtheschemesuggestedinchapter3.Someoftheintervieweeshavenotmadeanyexplicitcorrelationanalysisduringthepastfiveyears,butregularlydecidesonwhethertohedgetheirareapricerisks.

Thedecisiononwhethertohedgetheareapricerisksoftenseemtobeanapplicationofamarketview.Iftheriskofanunfavourablezonalprice(belowthesystempriceforproducers,abovethesystempriceforendusersandretailers)isconsideredlow,aseeminglyattractivechoicecanbenottohedgetheareapricerisk,andretainanopportunitytobenefitfromafavourablepricedifferenceinstead.Amarketviewisestablishedwheninternalortrustedpriceprognosesarecomparedwithcurrentmarketprices.Correlationanalysescanbeintegratedinthedevelopmentofpriceprognoses.Modelsthatonlyforecastlocalpricescanbecombinedwithcorrelationanalysestoproduceaforecastforthesystemprice.

Iftheareapricerisksarehedgedbyproxies,acommonconcernistheremainingunhedgedzonalrisksinthe‘homemarket’andsomezonalrisksrelatedtotheproxy.Thelattergroupof‘external’riskscanbedifficulttoexplaintostakeholders,andmightalsobeblurredinthehedgeportfolio.Itwillnotnecessarily‘help’iftheproxycontractisveryliquid,tradedwithminimumbid/ask-spreadandhasanicetrackrecordofgoodcorrelationwiththelocalmarket.Theproblemisratherthatthehedgeincludesrisksthatarenotnaturallyapartofthehedgedoperation.

2.4 Jetfuelhedgingstrategiesintheaviationindustry

Jetfuel(akerosenetypefuel)isamajorcostitemintheairlineindustry.Itspercentageofoperatingcost,whichisthemostcommonmeasure,variesalotbetweenairlinesandisdependentoftheroutestructurewherethemixofshorthaulandlonghaulproductionhasalargeimpact.Furthermoretheaircraftfleetcompositionisimportantwhereneweraircrafthasadistinctadvantageinfuelefficiency.Anotherobviousrelationshipisthecostefficiencyinotherareassuchasadministrativeoverhead,labourcostandfleetcommonalitywhenfuelcostislookeduponasapercentage.

TypicallythishastheeffectthatlowcostcarrierslikeRyanair,EasyjetandWizzAirshowsmuchhigherpercentagesoffuelcostscomparedtooperatingcoststhanthelegacycarrierssuchase.g.

BritishAirways,LufthansaandAirFrance-KLM.AsanexampletheleadinglowcostcarrierRyanair’sfuelcostin2014/15was43percentofitsoperatingcostversusanoldlegacycarrierasSASwheretheratioforthecorrespondingperiodwas24percent.Sincefuelcostdoesn’tvarysignificantlyovertimebetweenairlinesthisactuallysaysmoreaboutthecostefficiencyinotherareasthanfuel.

Theoverallobjectivementionedbytheairlinesthatdohedgethefuelexposureisnottoprofitbutrathertoobtainconsistentprotectioninordertoensureticketpricingpredictabilityandmaintainingequilibriumwiththecompetition.

Regardlessoftherelativeimpactofthefuelcostatanairlineitisstillasignificantcostitemwhichneedsmanagementattention.Althoughlogisticsanddistributioncostsamountstoroughly10percentofthetotalfuelcostintoday’smarkettheproductpricehasahugeimpactontheoverallcosts.Takingtheoilmarketvolatilityintoaccounttheonlywayofmanagingthiscostitemistohedgeaworldmarketrelatedportionofthefuelcost.

2.4.1 Thejetfuelmarketandtheoilmarket

Jetfuelisacomparativelysmallrefinedproducttypicallyrepresentingeighttotwelvepercentoftherefinedoilbarrel.Jetfuelisnotanexchangetradedcommoditycontrarytocrudeoil,gasoil(heatingoil)andgasoline.

ThepricingofphysicaljetfuelispredominantlypublishedviaPlatts(asubsidiaryofMcGraw-Hill)andbyOPISwhobasetheirpriceassessmentsofreportedphysicaltradesasindicesforthemajortradingcentressuchasARA(Amsterdam-Rotterdam-Antwerp),NorthWestEurope,USEastCoast,USWestCoast,USGulfCoastandSingapore.

WiththelackofexchangetradedfuturesthosewhowouldwanttodirectlyhedgeanyspecificjetindexmustresorttoOTCstructures.

TheoilmarketischaracterizedbyahighdegreeofvolatilityasillustratedinFigure2-1.

ThecrackspreadbetweenjetfuelandBrentisalsovolatileduetofluctuatingdemandandvariationinrefineryeconomics.ThisisshowninFigure2-2andFigure2-3.

Figure2-1Brentandjetfuelpricedevelopment

Figure2-2JetCrackSpread

Figure2-3YearlystandarddeviationfortheJet-Brentcrackspread

2.4.2 HedgingstrategiesbythreeEuropeanairlines

2.4.2.1 AirlineA

Thisairlineishedgingthejetfuel,amountingtoapproximately1.3millionmetrictonsofestimatedconsumptionperannum.Thepurposeistoobtainpredictabilitywhenpricingitsproducts,i.e.ticketstothemarket.

Thehedgingpolicyisdeterminedbytheboardandcanberevisedyearly.Thepolicystatesthat40to80percentshallbehedgedforwardona12monthsrollingbasiswithanoptiontohedgeanadditional50percentformonths13to18.HowthepercentagesareappliedoverthetimehorizonisdecidedbyitsFuelCommitteechairedbytheCFOandwithrepresentativesfromtreasury,thephysicalfuelpurchasingdepartmentandthecommercialdepartment.Thehedgesareexecutedandmonitoredbytreasury.

Thepolicysetsnolimitforpremiumcost;theamountsspentareattheFuelCommittee’sdiscretion.

Thereisahighdegreeoffreedomtouseabroadrangeofinstrumentsbutsellingcalloptionsnetisexplicitlyforbidden.TypicallythehedgesusedareamixofOTCswaps,outrightcalloptionsandzerocostcollars(seeillustrationsinFigure2-5toFigure2-7).

ProxiesareallowedandhistoricallyIPEGasoilhasbeenused.Currentlyallhedgesareinjet(JetFuelCIFCargoesNWE)whichisthisairline’sindexthatpricesitsphysicalfuelatitshomemarket.TheairlinehasasignificantamountofphysicalfuelpricedonotherindicesintheUSandSingaporebutthisbasisriskiscurrentlyignoredinordertominimizeadministrationandtransactioncomplexity.

UseofIPEBrentisalsoallowedbutthisisfurtherdiscussedbelowinconnectionwithaccounting.

Anydeviationfromthepolicyhastobeapprovedbytheboard.

Thisairlinehasaroundtencounterpartiesapprovedbythetreasurythattheycantradewithundercertainlimitsandthisisdeemedtobesufficient.Allcurrentlyapprovedcounterpartiesarebanks;theratingofthetwomajortradingoilcompaniesShellandBParenotmeetingtheairline’sratingrequirement.Sincethenumberofcounterpartiesisrelativelysmallandwellknown,nobrokersareusedsincetheyareonlyperceivedasanadditionalcostprovidinglittleifanyvalue.

BenchmarkingandsubsequenthedgeaccountingisperformedbasedonIAS39.TheinterpretationbytheauditorsisthatsufficientcorrelationisobtainedbyhedgesinjetandIPEGasoilbutthatahedgeinIPEBrentdoesnotqualifyforhedgeaccounting.ThisisthereasonwhyBrenthedgesarenotusedalthoughtheyareallowedbythehedgingpolicy.

Theoilmarketisconsistentlymonitoredandthedecisiontotakethedesiredhedgetransactiontothemarketisbasedonperceivedopportunityandthepolicy’srequirements.Therearenoindicationsthatanysophisticatedsimulationsandtechnicalanalysisisdonewithintheairline.

Hedgetransactionsare“tenderedinthemarket”i.e.severalprovidersareaskedtosubmittheiroffersandthemostcompetitiveofferisaccepted.

2.4.2.2 AirlineB

Thesecondairlineisthelargestofthethreestudiedairlines.IthasasimilarapproachtohedgingasairlineAabove.

Thepredictabilityoftheoilpricecomponentistheobjectiveforhedgingtheabout10millionmetrictonsofestimatedconsumption.

Thehedgingpolicyissetbytheexecutivemanagementandnotbytheboard.TheexecutivemanagementalsodecidesonanydeviationsrecommendedbytheFueldepartment,whichisresponsibleforexecutingthepolicyandalsoforpurchasingthecorrespondingphysicalfuel.

Thepolicystatesthat50percentshallbehedgedona24monthrollingbasiswithamaximumof80percentofanyonemonth.Additionalhedgesforadditional12monthsareallowedwiththesamepercentages.Additionalhedgesforlargechartercontractsarealsomadeifthecontractrevenueisfixed.

ThisairlineisusingproxyhedgingasdefinedbythepolicybyusingOTCswaps,calloptionsandzerocostcollarsinIPEBrent.

Thisuseofproxyhedgingmeansthatthisairlineisignoringthebasisriskbetweencrudeoilandjet(thejetcrackspread).Althoughthecrudeoilpricemovementsovertimemirrorthejetfuelpricemovements,thecrackspreadfluctuatesalotduetofluctuatingdemandandvariationinrefineryeconomics,seeFigure2-2.Uponadirectquestionitstatesthatitiscomfortablewiththatbasisriskexposure.Themainreasonforproxyhedgingisthatthecomparativelysmalljetmarketisilliquidlongterm(longtermmeaningafteroneyearforward)whereasthemuchlargercrudeoilmarketprovidessufficientliquidityuptofiveyearsforward.

AirlineBismoreexposedthanairlineAabovetojetpricingbasedonindicesinotherregionsthanEurope.ThisexposureinotherregionsisignoredalthoughthepolicyallowshedginginWTI(WestTexasIntermediate).WTIistheUSequivalenttotheEuropeanbenchmarkBrentcrudeoilandprovidesabettercorrelationtoUSjetindices.

ThisexposurewashandledbytheprevioushedgingpolicywhichwasdifferenttothepresentinthatthejetfuelcrackspreadwashedgedinadditiontoBrentforthenext6monthsforwardfor25percentoftheconsumptiononaveragewiththehighestcoverageinpromptmonths(Figure2-4).

Theairlinehasaroundtwentycounterpartiesapprovedbyitstreasuryavailableandthehighernumberisprobablyexplainedbythisairline’sowncreditratingandtheirownratingrequirements.Althoughthebanksareinmajoritytheyalsotradewiththeoilindustry.BrokersarenotusedduetothesamereasonsasexplainedaboveforairlineA.

AlsothisairlineperformshedgeaccountingbasedonIAS39.However,theirauditorsaresurprisinglyenoughsatisfiedthatIPEBrenthedgesprovidesufficientcorrelationtothejetfuelprice.

Figure2-4Mechanichedgingstrategyforjetfuelcrackspread

SameasairlineAabovetheyconsistentlymonitortheoilmarketandthedecisiontotakeadesiredhedgetransactiontothemarketisalsobasedonperceivedopportunityandthepolicy’srequirements.Althoughthisairlinehaslargerdedicatedresourcestofuelitdoesnotseemthatsophisticatedsimulationsandtechnicalanalysisaredone.

Thetransactionisinstead“tenderedinthemarket”i.e.severalprovidersareaskedtosubmittheiroffersandthemostcompetitiveofferisaccepted.Thisseemstobethecurrentstandardbusinessmodelintheairlineindustry.

Thisairlinealsohighlightedthecompetitivesituationversusotherairlines;“ifourcompetitorsdidnothedgeweprobablywouldn’teither”.

2.4.2.3 AirlineC

Thisairlinehasrecentlyundergonerestructuring,staffreductionsandchangesofstaffinfuelmanagementandfinance.Itwasmuchlessforthcomingthantheothertwotosharetheirpolicyandtheirmarketbehaviourwhichiswhythebelowismostlyderivedfromtheirlatestpublishedannualreport.

Theairlinehasreduceditshedgingoftheabout1milliontonsitconsumesduetoextensivehedginglossesincalendar2015.

Thehedginghorizonis24monthsforwardwithdecliningpercentagesovertimeandisregulatedbythehedgingpolicyapprovedbythedirectorsanddelegatedtoaFinancialRiskCommittee.

Contrarytothetwootherairlinestheyhavehistoricallyhedgedwithamixofjet,BrentandgasoilfortheirEuropeanjetconsumptionandheatingoilfortheUSportion.However,ifthisstrategyisstillusedisunclear.

InstrumentsusedaretheindustrystandardOTCswaps,calloptionsandzerocostcollars.

Interestinglythisairlinedoesnotusehedgeaccountingbutbooksthefairvalueofitshedgestotheprofitandlossaccount.Thisindicatesthatthisairlinehasnotgottenapprovalfromtheauditorstousehedgeaccountingdependingonthecommoditiestheyarehedgedwith.Anotherreasonispossiblythattheairlinehastwomajorownersandthattheyarenotconcernedwithvariationsintheprofitandlossaccountcausedbyhedges.

2.4.3 Commentsfromthebankingindustry

Asanadditionalsourceofinformationabouthedgingstrategiesofairlines,wehavealsointerviewedaderivativetraderinoneofthemajorUSbanks’commoditybranch.Thebankisoneoftheworld’slargestcommodityderivativeproviders.

Thelow-costsegmentoftheairlineindustryisgenerallyhedgedtoahigherdegreethanthelegacycarrierswhichisnotreallysurprisinggiventheformer’slow-costoffertothetravellingpublic.

ProductscommonlyusedareprimarilyBrentbutalsogasoilandjetareused.

Ifjetischosen,thehomemarketindexiscommonlyusedandthebasisriskversusotherregionalindicesisgenerallyignored.

However,thetrendofusingproxiesisdefinitivelytowardsusingBrentifhedgeaccountingwithBrenthedgesareaccepted.

Thereseemstobenostandardviewonthisandarumoursaysthatalargeairlineobtainedhedgeaccountingacceptancefromonecountrybranchofanauditorwhereasthiswasnotacceptedbyadifferentcountrybranchofthesameauditingfirm.

Creditriskisahugeissueforthehedgeproviders.Giventhefinancialstateoftheairlineindustryalotofcarrierscannothedgeduetotheirratingand/orperceivedfinancialstatus.

OnewayofresolvingthecreditissueistoembedtheoilderivativewithaCDS(CreditDefaultSwap)ontheairlineprovidedthataCDSonthespecificairlineactuallyexists.Obviouslythisaddstothecostofthederivativebutitdoesprovideanabilitytohedgeforalessfinanciallystableairline.

Thefollowingchartsoutlinethethreetypesofhedginginstrumentsthatarecommonintheairlineindustry.Thefirstisafixedpricestructurebymeansofjetswaps.Thesecondistogetapricecapbytheuseofcalloptionsandthethirdistouseacombinationoftwooptionsinorderthatresultsinazerocostcollar.

Figure2-5Fixedpricestructurebymeansofjetswaps

Figure2-6Pricecapbyjetcalloptions

Figure2-7Capandfloorestablishedbyazerocostcollarstrategy

2.4.4 Summaryandsimilaritieswiththeelectricitymarket

ThehedgingchoicesandhedgingstrategiesforjetfuelaresurprisinglysimilartothechoicesandstrategiesappliedbyindustrialcustomersintheNordicelectricitymarket.Jetfuelisanimportantcostitemintheairlineindustryaselectricityisforelectricity-intensiveindustries.TherelationshipbetweenJetandIPEBrentasillustratedinFigure2-2abovecanbeseenasasimilarrelationshipastherelationshipbetweenthesystempriceandthezonalprices.

Jetfuelisnotdirectlyexchangetraded.AnairlinewantingtohedgehasachoicebetweenaveryliquidproxyasBrent,aliquidproxyasgasoilorheatingoil,orratherilliquid,atleastlong-term,OTCswapsinjetfuel.ThereisalsoapossibilitytocombineveryliquidbasichedginginBrentwithsupplementaryhedginginshort-termOTCcrackspreadsbetweenjetfuelandBrent.

AnindustrialcustomerintheNordicmarkethasachoicebetweenaveryliquidproxyasthesystemprice,aliquidproxyasacombinationofsystempriceandanEPADforanothermoreliquidbiddingzone.ThereisalsoapossibilitytocombineveryliquidbasichedginginsystempricewithsupplementaryhedginginaperhapsilliquidEPADforitsownbiddingzone.

Mostairlinesandmostindustrialcustomersinelectricitywanttoavoidfluctuatingquarterandannualresultsbecauseoffluctuationsinthemark-to-marketvalueofjetfuelhedgesandelectricityhedges.ItisveryimportantforthemthattheirauditorsapprovethattheirhedgesarequalifiedforhedgeaccountingaccordingtoIAS39.Therefore,thechoiceofusingproxiesornotmainlydependsontheirauditor’sviewonthecorrelationbetweentheproxyandthehedgeditem.

Allthreeairlinespurchasephysicalfuelindifferentworldregionspricedondifferentindices,buttwoairlinesbaseallhedgingonthehomemarketindex.Theremainingbasisriskisignoredinordertominimizeadministrationandtransactioncomplexity.

Giventheexperiencesoftheoilmarketcrashinlate2008thedecisionontheexecutionofthehedgingpolicy–andnotonlythepolicyitself–hasincreasinglyinvolvedexecutivemanagementdirectlyorindirectlyviaahedgingcommittee.

The2008marketdevelopmenthasalsoledtoseveralairlines,primarilyintheUS,havestoppedhedgingtheirjetfuel.

Anothercommonreasonfornothedgingisthelackofcreditwiththebankingcommunity.

2.5 Hedgingstrategiesinthealuminiumindustry

TheNorwegianmetalsindustryisasignificantbuyerofelectricity.Electricitymaycountforasmuchas30–40%ofthetotalcosts.Investmentsinthissectorhavequitelongtimehorizons,

oftenbeyond20years.Investmentsarethusassociatedwithconsiderablerisks,alsoregardingelectricitycosts.

Awell-knownplayerinthismarketisNorskHydro.Someofthegeneralfeaturesoftheirhedgingphilosophyarepubliclyknown.OneoftheobjectivesforthehedgingactivitiesistosupportHydro’sattractivenessinthecapitalmarket.Hydrowantstoberecognisedasanindustrial,notafinancialcompany.Thisimpliesthattheycannothedgeallrisks,bothattheinputandattheoutputside.AsinvestorsinvestinHydroinordertobeexposedtotherisksinthealuminiummarket,itwouldhavebeencounterproductivetohedgethesaleofaluminium.

Butonthesupplyside,Hydroiswellknownforitslonghorizoninhedging.HydrowasamongthepioneersindevelopingtheNorwegianhydropowerresources.Withfullownershiptopowerplants,Hydrohaslargelyinternalisedmajorriskfactorsforthecostside.In2011,NorskHydropurchasedtheBraziliancompanyValeS.A.’saluminiumbusiness,therebyalsogainingcontroloverHydro’ssupplyofbauxite.NorskHydroseemstopursuesimilar(atleasttosomeextent)hedgingphilosophiesinthemarketsforpowerandforrawmaterials.

AsHydro’sannualpowerconsumptionintheNordicregionissignificantlyhigherthantheirownpowergeneration,NorskHydroisalso‘constantly’lookingforlongtermpowercontracts.Thisisnotaminorchallengeastheirpotentialcounterparts,theutilities,havesimilarconcernsintheirhedgingphilosophies–sellingpowercontractswithrelativelyfixedpricesorpriceformulasforadecadeortwoimpliesthattheirownersnotnecessarilygetwhattheyareexpectingasownersofutilities.Nevertheless,itiswellknownthatHydroeverysooftenhavesigned20yearcontractsforannualquantitiesofupto1TWh.

Hedginghorizonsof20yearsormorearefarbeyondallexchangebasedfinancialmarkets.Hydro’sonlyoptionisthustonegotiatebilateralcontractswithcounterpartiestheytrust.Insuchdeals,theymayormaynotagreeonadeliverypointorreferencepriceatthelocationofHydro’sfactories.Eitherway,EPADsorSYScontractsarenotparticularlyrelevantfortheirhedgingstrategy.However,the‘problem’isnotthepricebehaviourortheefficiencyofthecontracts,butthemuchshorttimehorizonfortheorganisedandtransparentmarketplaces.

TheexampleofNorskHydroillustratesthatfinancialcontractsmaybeirrelevantforsomehedgingrequirementsevenifthecontractswereperformingperfectlyinallotheraspectsthantimehorizon.Theexamplealsoillustratesthatthehedgingopportunitiesarenotlimitedtocontractslistedatexchangesandclearedbyclearinghouses.Interestingly,thesituationforcompaniesinsimilarsituations,withhedginghorizonsofmanyyearsratherthanafewyears,isnotimprovedoraddressedbytheFCAGL.

2.6 ConclusionsKeyfeaturesofhedgingstrategiesinseveralsectorsarethattheyarepragmaticandinformal.

• Pragmaticmeansthatriskmanagementisatoolandnotagoalperse.Companiestendtomaximiseprofitswithinconstraints,andrisksareonegroupofconstraints.Thechallengeisthereforetofindtheacceptablelevelofriskforacceptablecosts.Therearenumerousexamplesofpotentialhedgesthatarenotused–simplybecausethecostsareconsideredtoohigh.‘Costs’hereincludesbothanapparentlyhighriskpremiuminacontract,thatthehedgemayreducenegativerisksbutatthesametimeforecloseattractiveprofitopportunities,andtheinternaladministrativecostsofmanagingacomplexhedgeportfolio.

• Pragmaticalsomeansthatwhenexecutingthehedgingstrategies,riskcommitteesarecommonlyinvolved.Thisreflectsthatmarketparticipantsoftendonothaveclearthresholdsorlimitsdictatingwhattodo.Afrequentfeatureofhedgingstrategiesisthatcompaniestendtoapplysomesortofmarketview.Thismeansthathedgingdecisionsmaybedependenton(internal)priceprognoses.

• Pragmaticfurthermeansthatmanycompanieswanttoavoidfluctuatingquarterandannualresultsbecauseoffluctuationsinthemark-to-marketvalueoftheirhedges.ItisimportantforthemthattheirauditorsapprovethattheirhedgesarequalifiedforhedgeaccountingaccordingtoIAS39.Therefore,thechoiceofusingproxiesornotmainlydependsontheirauditor’sviewonthecorrelationbetweentheproxyandthehedgeditem.

• Informalmeansthatthehedgingismostoftennotbasedonformalcorrelationormarketanalysis.

• Informalpartlyreflectstheinvolvementofriskcommitteesetc.,butalsothatanalyses,iftheyareperformed,tendtobeadhocortailormade,andnotperformedatfixedorregularintervals.

3 Measuringrelevanceofhedgeinstruments

Thefirstanalysiscalledforinarticle30(4)iswhetherappropriate(effective)hedgesforday-aheadpricerisksareavailableformarketparticipants.IfEPADsorotherlocalfinancialcontractsareavailable,theappropriatenessofthesehedgingopportunitiesisnotanissue–thesearebyconstructioneffectivehedges.AshortorlongpositioninanEPADincombinationwithasystempricecontractwillperfectlyeliminateanypriceriskinthecontractperiod.Thesameholdsforshortorlongpositionsine.g.Dutch,GermanorBritishfuturescontracts.

Theanalyticalchallengecomesiftherearenolocalfinancialcontractsavailableorifthelocalfinancialcontractsareconsideredinefficient(seechapter4).Marketparticipantswithhedgingdemandswilltheneventuallylookforproxies–i.e.othercontracts,eitherbythemselvesorincombination,thatpotentiallycouldprovideappropriatehedges(Alexander,2008).ForaNordicbiddingzone,thatcouldbeanEPADforanotherbiddingzonewithcomparablebehaviourofday-aheadprices.Alternatively,onecouldlookforacombinationofseveralcontracts,suchastwoEPADs,oneEPADandonelocalfuturescontract,oranyothercombinationthatappearstoprovideappropriatehedge.

Itisnotrequiredthattheproxyisforanadjacentbiddingzone.Theimportantissueiswhetherashortorlongpositionintheproxyprovidesufficienthedgeforthemarketparticipant.Asthisisafinancialmatter,thephysicallocationoftheproxyisnotanissue.Itisthebehaviourofthepricesthatmatters.

Inthischapterwediscusshowtodetermineifavailableproxieshavesufficientcorrelationwithazonalprice.Westartwithamathematicalapproachtodescribethevolatilityoftherevenueforamarketparticipantwithdifferentchoiceofhedginginstruments.Therelevantmethodsforquantitativeassessmentsfollowimmediatelyfromthemathematics.

3.1 Thecorrelationanalysisdependsonthehedgingstrategy

Apracticalinterpretationofpriceriskistowhichextenttherevenuevarieswithfluctuatingprices.Acommonmeasureofsuchvariationsisthestandarddeviationoftherevenue.Iftherevenueisfullydeterminedbythepricesinhedgingcontracts,theimpactofshort-termpricevariationiseliminated,andthestandarddeviationislow.Toprepareforananalysisofhowtomeasurehedgeeffectiveness,westartwithsomemathematicsderivationstostudytherevenueinsomedetail.

3.1.1 HedgingwiththerelevantEPAD

Considerapowerplantwithdeliveryinbiddingzonez.Let𝑧"representthe(average)priceinperiodtinbiddingzonezand𝑠"representthesystempriceinperiodt.Letusdefinethezonaldifferenceasthedifferencebetweenzonalpricezandthesystemprices.TheunderlyingforanEPADisthezonaldifference:

𝑑"% = 𝑧" − 𝑠" (1)

Thezonalpriceinperiodtcanthusbewrittenas

𝑧" = 𝑠" + 𝑑"% (2)

LetusassumetheownerconsidershedgingtheoutputfromthepowerplantbysellingaSYScontractandanEPADforzonez.Themarketpriceatthetimeofhedgingis𝑆fortheSYScontractand𝑍fortheEPAD.Settlementofthehedgingcontractsduringthedeliveryperiodsyieldsthefollowingpayment:

𝑆 − 𝑠" + 𝑍 − 𝑑"% (3)

Thetotalpaymenttothepowerplantisthesumofthephysicaldeliveryandthesettlementofthehedge:

𝑧" + 𝑆 − 𝑠" + 𝑍 − 𝑑"% = 𝑠" + 𝑑"% + 𝑆 − 𝑠" + 𝑍 − 𝑑"% = 𝑆 + 𝑍 (4)

Aswecansee,thefinalrevenueisconstantandindependentfromboththeactualzonalpriceandthesystemprice.Thestandarddeviationofthedeliverypricesduringthehedgingperiodisthuszero.ThusthereisnoneedtoworryaboutcorrelationoreffectivenessofthehedgeifthereisanEPADavailable.

3.1.2 HedgingwithanotherEPAD

Alternatively,theownerconsidersusingtheEPADforzonex.Usingthesameprinciplesfornotation,thesettlementofthehedgecannowbewrittenas

𝑆 − 𝑠" + 𝑋 − 𝑑", (5)

Thetotalrevenuewillnowbethesumofthehedgepricesandthespreadbetweenthezonaldifferences.

𝑧" + 𝑆 − 𝑠" + 𝑋 − 𝑑", = 𝑠" + 𝑑"% + 𝑆 − 𝑠" + 𝑋 − 𝑑", = 𝑆 + 𝑋 + 𝑑"% − 𝑑", (6)

Thespreadbetweenthezonaldifferences,𝑑"% − 𝑑",,isequaltothespreadbetweenthezonalprices

𝑑"% − 𝑑", = 𝑧" − 𝑠" − 𝑥" − 𝑠" = 𝑧" − 𝑥" (7)

Asthepricesinthehedgecontracts,𝑆 + 𝑋,isaconstantwhenthehedgeismade,thestandarddeviationoftherevenuedependsonthecorrelationofthezonalprices.Mathematically,thevarianceoftherevenueequals

𝑉𝑎𝑟 𝑆 + 𝑋 + 𝑧" − 𝑥" = 𝑉𝑎𝑟 𝑧" − 𝑥" = 𝑉𝑎𝑟 𝑧" + 𝑉𝑎𝑟 𝑥" − 2𝐶𝑜𝑣 𝑧", 𝑥" (8)

Thestandarddeviationisthesquarerootofthisexpression.Thecorrelationbetweenzandxisdefinedastheratiooftheircovarianceandtheproductoftheirindividualstandarddeviations;

𝐶𝑜𝑟𝑟 𝑧", 𝑥" =𝐶𝑜𝑣 𝑧", 𝑥"𝜎% ∙ 𝜎,

Thiscanberearranged,suchthat𝐶𝑜𝑣 𝑧", 𝑥" = 𝐶𝑜𝑟𝑟 𝑧", 𝑥" ∙ 𝜎% ∙ 𝜎,,andthenwecanseehowthecorrelationmetricfitsintothecalculations.

Ifzandxareperfectlycorrelated,thecovarianceequalstheproductoftheindividualvariances,whichalsoareequal.Inthatcase,thevariance,andthusthestandarddeviation,oftherevenueiszero.Ifzandxarenotcorrelatedatall(correlationcoefficientandcovarianceequaltozero),thenegativeelementontheright-handsideinEquation8iszero,whichclearlymakesthevarianceandstandarddeviationlargerthanifzandxareperfectlycorrelated.FindingagoodproxythusimpliessearchingfortheXinthesetupherethatminimisesthevariance.

Themean-varianceandportfolioapproachtohedging(section2.1)showsthatcompleteeliminationofriskisnotoptimal,butratherthathedgingafractionoftheportfolioeitherdirectlyorindirectlythroughproxiesyieldthe“highestpay-off”tothehedger.

3.1.3 Otherhedgingstrategies

AnotherhedgestrategywouldbetorelyonSYScontractsonly,inwhichcasetherelevantcorrelationtostudyisthatbetweentheactualdeliverypricezandthesystemprices.Hence,the

approachisquitesimilartotheanalysisofahedgerelyingonanEPADforanotherzonethanthedeliveryzone.

AvariantoftheabovehedgingstrategyistocombineseveralEPADs.ThatcorrespondstoreplacingXwithaweightedaverageofothercontracts.Theprinciplesarestillthesame.

AfurthervariantwouldbetocomposeahedgeportfoliomixingbothSYScontracts,EPADsandfinancialcontractsforotherareas,e.g.theGermanortheDutcharea.

3.2 Correlationanalysisinpractice

Theequationsaboveraisesomeimportantquestions.Oneisabouttimeresolution,anotherisaboutwhatisconsideredas‘good’orsufficientcorrelation.WestartwithdescribingNordictradingvolumesandhedgingvolumesfordifferentcontractdurations.Wecontinuediscussingwhethertorelyonthepracticethatstemsfromhedgeaccountingtestsandstudythecorrelationbetweenchangesinpricesfromoneperiodtoanother,oralternativelystudythecorrelationbetweenthepricesdirectlyastheequationstell.Finally,wediscusspracticaldetails,suchaswhichpricesarerelevantandhowtodetailtimeresolution.

3.2.1 Tradingvolumesandopeninterestfordifferentcontractdurations

Figure3-1showsfordifferentcontractdurationshowclearedtrades(TWhpermonth)hasdevelopedduring2013-2015intheNordicmarket.Asfarasweknow,allOTCtradeintheNordicregioniscleared.Quarterlyandyearlycontractshavethehighesttradedvolumes.Thevolumesinweeklyanddailycontractsarenearlynegligible.

Figure3-2showsafairlystablelevelofopeninterest–thetotalopeninterestfluctuatesbetween250and300TWh.Astrikingdifferencewhencomparingthetwodiagramsisthatwhileyearlyandquarterlycontractsaretradedinapproximatelysimilarvolumes,theyearlycontractshaveamuchhighershareoftheopeninterest.ThisindicatesthatintheNordicregion,theyearlycontractsaremoreusedforhedging,whilespeculativetraderstendtofocusonquarterlycontracts.

Figure3-1Tradedvolumesfordifferentdurations,NordicSYScontracts(Datasource:Nasdaq)

Figure3-2OpeninterestinNordicSYScontracts(Datasource:Nasdaq)

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2013 2014 2015

Clearedtrades,SYScontracts[TWhpermonth]

WeeksandDays Months Quarters Years

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2013 2014 2015

Openinterest,SYScontracts[TWh]

WeeksandDays Months Quarters Years Total

Figure3-1andFigure3-2reflectthetradeofsystempricecontracts.SimilardiagramsforEPADsareprovidedbelow.

Figure3-3Tradedvolumesfordifferentdurations,EPADs(Datasource:Nasdaq)

Astrikingdifferencebetweenthisfigureandfigure3-1isthatwhilequarterlyandyearlySYScontractsaretradedinsimilarvolumes,thetradeinEPADsisdominatedbyyearlycontracts.Further,comparingFigure3-2andFigure3-4,wecanseeanalmostidenticaldistributionofopeninterest(ondifferentdurations)onEPADandSYScontracts.Takentogether,thissuggeststhatwhilethesystempricecontractsarepopularfortrading,theprimaryuseofEPADsisforhedging.

Frombothdiagramsofopeninterest,itisalsofairlyeasytoseehowopeninterestinyearlycontractsareturnedintoopeninterestinquarterlycontractsbeforeyearend(thecascadingeffect),butthetotalopeninterestisfairlystable.

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2013 2014 2015

Clearedtrades,EPADs[TWhpermonth]

Weeks Months Quarters Years

Figure3-4OpeninterestinEPADs(Datasource:Nasdaq)

3.2.2 Correlationbetweenpricesorpricechanges?

Thecorrelationtestsintheaccountingliteraturearecomparingthechangesinmark-to-marketvaluesofahedgeditemandaportfolioofhedgingcontracts(Finnerty&Grant,2003;Hailer&Rump,2005).Thereasonisofcoursethatthestartingpointfortheaccountsisthatallcontractsshouldbebookedatmark-to-marketvalue.Thisappliesinparticulartoderivativesthatarelistedatexchangeswithpubliclyknownandacceptedpricequotes.IAS39allowsforanexemptionfromthisgeneralruleifthemark-to-marketvaluesofthetwo(thehedgeditemandthehedgingportfolio)aresufficientlycorrelated.Theexemptionimpliesthatadecreaseinthevalueofe.g.thehedgeportfoliodoesnothavetobebookedagainsttheprofitandlossaccountbecausethelossalsoreflectsasimilargaininthevalueofthehedgeditem(andviceversa).Withoutanexemption,thelossonthehedgeportfoliomustbebookedimmediately,whilethecorrespondinggaininthehedgeditemcannotbebookedduetothegeneralprinciplesofcautiousaccounting.Thecorrelationtestsmustthereforefocusoncomparingthechangesofpricesfromoneperiodtothenext.

Thehedgingdecisionsintheelectricitymarkethaveadifferentperspectiveandobjective.Theobjectiveisgenerallytoreducethevolatilityofrevenueorcostsduetothevolatilityofday-

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2013 2014 2015

Openinterest,EPADcontracts[TWh]

Weeks Months Quarters Years Total

aheadprices.Andwithproperhedgingcontracts,themarketparticipantcan‘replace’thevolatileday-aheadpriceswithfixedpricesforlongerperiods.Therewillstillbevolatilityinrevenueorcostswithsuchhedging,butthevolatilitywillbelowerandthepriceswillbemorepredictable.

Thisobjectiveorstrategyisreflectedinthemathintheprevioussection.Thereitfollowsimmediatelythatwhatmattersisthecorrelationbetweentheaveragedeliverypriceofthehedginghorizonandtheaverageoftheunderlyingforthehedgingcontractsoverthesameperiod.

Anotherwaytoexplainthisisthatoncethehedgeismade,itdoesnotmatterifthemarketpricesforthehedgingperiodchanges.Ifamarketparticipanthassoldatsay20EUR/MWhfornextyear,andthemarketpriceforsuchcontractsincreasesto21EUR/MWhthedayafter,thisincreasehasnoimpactonthefuturerevenue.Thehedgedvolumewillonlyreceive20EUR/MWh.Theincreasefrom20to21EUR/MWhisrelevantonlyforamark-to-marketvaluation,notforpredictingthefuturerevenue.

Thescopeforthecorrelationanalysismustthereforebetocompareagivenzonalpricewiththeunderlyingforappropriatehedgingportfolios.Theconcerniswhetherthepricesinthedeliveryperiodarewellcorrelatedornot,andnotwhetherchangesinthevalueofthehedgingportfolioandthehedgeditemduringthehedgingperiodarecorrelated.Thustheapproachinaccountingtestsisnotrelevantinthiscontext.

3.2.3 Whichpricesshouldbecompared?

ItfollowsfromthebeginningofthischapterthatiftherelevantEPADisconsideredefficient,thereisnoneedforacorrelationanalysis.ThedeliverypriceandtheunderlyingforahedgebasedonaSYScontractandthesaidEPADarethesame.ThecorrelationanalysisbecomesrelevantifthelocalEPADisconsideredinefficientorthereisnolocalcontractavailable,andaproxyisconsideredinstead.Theanalyticalproblemisthenthattherecanbeaninfinitenumberofproxies,orpotentiallyrelevanthedgeportfolios.Thefocusintheliteratureisonamean-variancehedgingwithaminimumvariancecriteria(Alexander,2008).

AhedgeportfoliocanconsistofSYScontractsincombinationwithseveralEPADs,andcanalsoincludee.g.GermanorDutchcontracts.Ifweconsiderahedgefore.g.SE1,onealternativecouldbetousetheHelsinkiEPAD.AnotheralternativewouldbetousetheStockholmEPAD.Wecouldalsocombinethemwithx%ofthevolumehedgedbytheHelsinkiEPADand100minusx%hedgedbyStockholm.AndwemightaswellconsiderincludingtheTromsøEPADinadditiontoHelsinkiandStockholm–orinsteadofStockholm.

Inpractice,wecanseeonlytworealisticapproachesfortheregulatorstosearchforpotentiallyrelevantproxies.Oneistoaskmarketparticipantswhichcontractstheyconsiderrelevantintheirhedgeportfolios.Theotheristosearchsystematicallythroughalimitedsetofalternativecombinations.Indoingso,theanalyticalchallengeis‘reduced’tofindthecombinationofcontractsthedemonstratesthebestcorrelationwiththelocalpricetobehedged.

Thisleavesuswiththetwoinitialquestions:Whattimeframesshouldbecompared,andisitpossibletodefineathresholdtodistinguishbetweensufficientandinsufficientcorrelation?

3.2.4 Timeresolutionandtimehorizon

Nordictradingvolumesandhedgingvolumesfordifferentcontractdurationsarebrieflydescribedinsection3.2.1.Hedginghorizonsareapparentlysomewherebetweenamonthortwo(short-termretailcontracts)andupto3-5years.Someproducershadhedgedtoomuchinadvancetobenefitfromtherelativelyhighpricesin2010and2011,andthinkthatthiswasnotonlyunluckybutalsoundesirable.Thuscurrently,someofthemmightbeabitreluctanttohedgetoofaroutintime.Thispartlyalsoexplainswhyhedgingstrategiesamonggeneratorsoftenareflexible.Typically,thestrategystatesthatbetweenxandy%oftheexpectedgenerationshouldbesoldoneyearahead,andfurtherthatbetweenzandv%shouldbesoldouttwoyearsahead,etc.(xandyarethenlargerthanzandv,respectively).

Exceptforthelongtermindustries,likemetals,industrialcustomershavesomewhatsimilarhedginghorizons,butfrequentlylessflexible.Retailersalsogenerallyhaveamoremechanicalapproachandahedginghorizoncorrespondingtothedurationoftheirfixedpricesalescontracts.

Forthosewithahorizonofseveralyearsitisgenerallytheaveragepriceperyearthatmatters,whilethequarterlyandevenmonthlyaveragesaremorerelevantforretailers.Wecannotseeanyreasontostudyaveragesovershortertimeperiods,suchasweeks.Hourlypricesareanywaytotallyirrelevant.

Apracticalapproachwouldbetostudybothyearlyandmonthlyaverages.ThisalsoenablesacomparisonwithLTTRswhichareyearlyandmonthlycontracts.Anissuewithyearlyaveragesisthatwemayhaveinsufficientdatapointstodoaproperanalysis.Analternativecouldthereforebetostudyquarterlyorhalf-yearlyaveragesinsteadofyearly.

Thenextissueishowmanytimeperiodstheanalysisshouldconsider.Acompanyconsideringahedgeisessentiallyconcernedaboutfuturedeliveryprices,notthepastones.Butitisthehistorythatisknownanditmighttellquitealotaboutwhatmayhappeninthefuture.Simplycomparingtheaveragepricesforthelastyearisclearlymisleading,particularlyifthehedging

horizonindicatesthatyearlyaveragesistherelevanttimeresolution.Includingallavailablepricehistoryorputtingequalweightontherecentyearsasontheoldestobservationsmightalsobemisleading.Apropercorrelationanalysisthereforereliesonabalancebetweennotlookingtoofarbackandnotmissingrealisticbutnotfrequentincidents(blackswans).

Apracticalsolutioncouldbetolooksomeyearsbackbutalsostudypreviouscorrelationscores.Supposeasanexamplethatwestudythepast48months,andthatwecalculatethecorrelationcoefficientbetweentwopriceseries.Wecanthengoonemonthbackandrepeatthecalculation.Wecanrepeatthisandstudyhowa48monthcorrelationfigurehasdevelopedovertime.

3.2.5 Nothresholds

Thelastandperhapsthetrickiestquestioniswheretodrawthelimitforasufficienthedge.Thebeautyoftheprinciplesfromhedgeaccountingisthatthereisanorm.Toqualifyforhedgeaccounting,thecorrelationcoefficientmustbeatleast0,8.MarketparticipantsintheelectricitysectormayhedgeatlowercorrelationrateswithouthavingtocomplywiththeIAS39iftheydonotapplyhedgeaccounting.Thusitseemsfairtoassumethataratiobelow0,8canalsobesufficient.0,7isclearlybetterthane.g.0,5,butis0,5sufficient?Andwouldhedgingbyaproxywithacorrelationcoefficientof0,5beworsethannothedgingthezonalpriceriskatall?

Onemightaskmarketparticipantswhatthresholdstheyapply(ifany)orwouldprefertheregulatorstoapply,butexperiencesuggeststhatmarketparticipantslookforprotectionfromunfavourableoutcomeofthezonalpricedifferenceandarethusmoreconcernedabouthowtheyconsidertheprobabilityforfuturepricemovements,ratherthanrelyingonacorrelationtest.Marketparticipantsmayalsohavevestedinterestsintheregulators’evaluationaftersuchasurveyorconsultation.

Ultimately,whethertoapplyandwheretodefineathresholdmustbeadecisionbytheregulator(s).However,werecommendthatknock-outthresholdsarenotused.Possiblethresholdsshouldonlybetreatedasindicatorsintheanalysis.Itistheoverallresultsfromcorrelationanalysis,efficiencyanalysisandconsultationthatisimportant.

3.3 SummaryofsuggestedmethodThemean-varianceapproachtohedginghasanimportantimplicationfortheassessmentofhedgingopportunitiesintheelectricitymarket.Usingastandardmean-varianceanalysisthecompositionandperformanceofselectedportfolioswithsystempricecontractsandEPADscanbeanalysedandevaluated.

Wesuggesttheregulatorscompareyearlyandmonthlyaveragezonalpriceswithsimilaraveragesoftheunderlyingforpotentialhedginginstruments,suchasSYScontracts,EPADs,andcontractsforadjacentbiddingzoneslikeGermany,oracombinationofsuchcontracts.Amethodicalchallengeisthatthereisessentiallyaninfinitenumberofpotentiallyrelevantcombinations.Thepurposeoftheanalysesmustbetotestwhetherthepricesinthedeliveryperiodarewellcorrelatedornot,andnottoexaminethechangesinthevalueofthehedgingportfolioandthehedgeditemduringthehedgingperiod.Hence,theapproachtakeninthehedgeaccountingliteratureisnotrelevantformeasuringcorrelationintheregulators’assessments.

4 Evaluationofcontractefficiency

Article30(4)bintheFCAGLcallsforananalysisofwhethertheproductsorcombinationofproductsofferedonforwardmarketsareefficient.InthischapterwediscussthechoiceofmethodstoanalyseefficiencyofcontractsrelevantforhedgingNordicelectricitypricerisks.Thereisarichliteratureonmeasuringcontractefficiencyinfinancialmarkets,andthusalargenumberofalternativeapproachesfortheregulators’analyses.Weoutlinethepotentiallymostrelevantliquidityandefficiencymeasuresforelectricityderivativescontracts,discusstheirbenefitsandlimitationsunderdifferentcircumstances(suchasgeographicalregion),concludeonwhichmethodstheregulatorsshouldapply,andprovidetechnicalguidanceontheirassessmentandinterpretation.

Wedistinguishbetweenthreegeneralclassesofliquidityandefficiencymeasures,heredescribedas1)Descriptivemeasures(tradinghorizon,tradedvolume,andopeninterest);2)Pricemeasures(riskpremium,long-andshort-runmarketefficiency,andAmihud);and3)Transactioncostmeasures(bid-askspreads,andRoll’smeasure).Theobjectiveisnottoprovideanexhaustivelistofallpossibleefficiencymeasuresortrytoidentifyasingleempiricalproxythatcouldcaptureallaspectsofefficiency.Instead,wediscussin-depthapplicationofafewmethodsandproxiesempiricallyapplicabletotheNordicelectricitymarkets.

Mostofthemeasuresdiscussedinthischapterevaluateasinglecontracttypethatcanbestudiedinthecontextofaparticularbiddingzoneandovertime(e.g.quarterlybaseloadfuturesinFinlandoverayear).Portfoliosorcombinationsofcontractsarediscussedonlypartially.Thereasonforthisapproachissimplytoavoidtoocomplexexplanations.Itshouldbenotedthatifaparticularcontractlateridentifiedasmis-pricedortoocostlywouldbeusedinaportfolio,thenegativeaspectsofsuchcontractcanbereducedbuttheywillnotsimplydisappearbypoolingthecontractwithotherhedgingcontracts.

Basedonthedetaileddiscussioninthissection,ourrecommendationistouselesscomputationallyintensiveliquiditymeasureswhicharemoreoperational.Therecommendedliquiditymeasuresareallofthedescriptivemeasures,riskpremiumfromthepricemeasures,andbid-askspreadsfromthetransactioncostmeasures.AbriefsummaryofallthemeasuresdiscussedinthischapterarepresentedinTable4-1.

Thechapterisorganisedasfollows:Section4.1providesabriefintroductiontoconceptsofliquidity,marketefficiency,andderivativespricinginelectricitymarkets.Wecontinueinsection4.2withthedescriptivemeasuresandinsection4.3withpricemeasures.Transactioncostmeasuresarediscussedinsection4.4.Anoverviewofourrecommendationsispresentedinsection4.5.

Table4-1Summaryofefficiencyandliquiditymeasures

Measure Interpretation Assessment Pros Cons

riptiv

Trading horizon

Measures product design

Descriptive analysis

Evaluation of hedging possibilities against individual contract time frames

Not a direct measure of efficiency or liquidity

Traded volume

Measures liquidity

Descriptive and time series analysis

Data availability (daily returns and volume)

Partial measure of liquidity

Open interest

Measures liquidity and importance for hedging

Descriptive analysis

Dynamic measure of liquidity and importance for hedging

Partial measure of liquidity

Risk premium

Measures hedging pressures

Time series analysis

Computationally straightforward

Needs further disentanglement

Amihud Measures liquidity

Data availability (daily returns and volumes); allows studying time series effects of liquidity

Not well defined for power derivatives markets

Long-and short-term market efficiency

Measures overall market efficiency

Data availability; allows testing overall market efficiency in short-and long-run

Analytical complexity; more reliable estimates for shorter maturity contracts due to smaller forecast errors

Bid-ask spread

Liquidity measure with pronounced effects on transaction costs

Descriptive and time series analysis

Measures the costs of hedging for market participants

Limited data access and availability of OTC bid-ask spreads (except for regulators)

Roll’s measure

Measures transaction costs

Infers a measure of effective bid-ask spreads simply from market prices

Relative ease of access to bid-ask spreads from market data

4.1 Backgroundonliquidity,efficiencyandpowerderivativespricing

Afinancialassetisperceivedliquidbymarketparticipantswhentheycanquicklyselllargeamountsoftheassetwithoutnegativelyaffectingitsprice.Typicalqualitiesofaliquidassetare1)smalltransactioncosts,2)easytradingandtimelysettlement,and3)largetradeshavingonlylimitedimpactonthemarketprice.Additionally,thefollowingfivecharacteristicsareassociatedwithliquidmarkets(Sarr&Lybek,2002):

1. Tightness–lowtransactionandimplicitcosts

2. Immediacy–speedwithwhichorderscanbeexecuted;efficiencyoftrading,clearing,andsettlementsystems

3. Depth–existenceofabundantordersaboveandbelowthecurrenttradingprice

4. Breadth–ordersarenumerousandlargeinvolumewithminimalimpactonprices

5. Resiliency–quickflowofneworderscorrectingorderimbalances

Someliquidityandefficiencymeasuresalsorelyontheassumptionofmarketefficiency.Theefficientmarkethypothesisinitsstrongform(FamaE.F.,1970)stipulatesthatsecuritypricesfullyreflectallavailableinformation,andinitsweakform(FamaE.F.,1991)thatthedeviationsfromthestrongefficiencyarewithininformationandtradingcosts.Ingeneral,returnsareclosetounpredictable(Cochrane,1999),followingarandomwalk.Thetheoryalsoholdsthatpricesarerationallydetermined,e.g.companiescorrectlyassesstheirrisks,andanydiscrepancybetweenthespotandderivativespriceswillbearbitragedaway.Nonetheless,pastevidence(Fama&French,1988;Campbell&Shiller,1988)suggeststhatreturnscanbereasonablywellpredictedforlonger-horizons(years)butlesssoforshort-horizons(daily,weekly,andmonthly).

Electricityderivativescannotbepricedinaccordancewiththetraditionaltheoryofstorage,becauseelectricityiseconomicallynon-storable.Instead,thepriceofelectricityderivativesisdeterminedbyexpectationsandriskpreferencesofmarketparticipants(Dusak,1973;Breeden,1980;Cootner,1960).Hence,thevariationinelectricityderivativespricesisdrivenentirelybytheexpectationofthefuturespotprice𝐸(𝑆𝑇|𝜴𝑡)duringthetimeofdelivery(T)conditionalontheinformationset𝜴𝑡availableattimetplusariskpremium,seeEquation10.Theriskpremiumrepresentsanequilibriumcompensationforbearingthepriceriskfortheunderlyingcommodity,i.e.electricity(Longstaff&Wang,2004,p.1887).

Ft, T = E(ST|Ωt) + πt (10)

Whenevaluatingthepriceofahedginginstrument,alinkwiththeunderlyingbusinessconditionsandfundamentalfactorsmustbeestablished.Inelectricitymarkets,thisincludes,forexample,theexpectedpricevolatility(priceskewness),weatherconditions(precipitation,wind,

temperature,etc.),largegenerationinvestmentsorshutdowns,newtransmissionlinesandtheirfaults,etc.

Hence,theultimatequestion,“Whatisareasonablepriceforahedge?”hastobeevaluatedunderagiventechno-economiccontextbecausethiscontextaffectstheexpectationsandrisksthemarketparticipantsreflectinderivativeprices.Also,theunderlyingmicrostructureofthepowerderivativesmarket,suchasproductdesign,marketparticipants,tradingsystems,clearingandsettlementoftransactions,andaccountingframeworkshouldbeconsideredwhenevaluatingliquidity.

4.2 Descriptivemeasures

Wecallthemeasuresinthisclassdescriptivebecausetheydonotrequireanytransformationorcomplexcomputationandcanbedirectlyinterpreted.Theinputsforthemeasuresinthisclasscomedirectlyfromthemarketdatapubliclyquotedbyanexchange,orotherwiseobtainedfrombrokersandinformationproviders.Thefirstmeasurediscussedbelowistradinghorizon,whichisaninstitutionalmicrostructurefactorshapingtheproductdesign(maturity)ofindividualderivatives.Thesecondandthirdmeasure,namelytradedvolumesandopeninterestarevolume-basedmeasures.Theyareusefulformeasuringmarketsignificanceandmarketbreadth,i.e.theexistenceofnumerousandlargeordersinvolumewithminimaltransactionpriceimpact.Relevantliteratureforthissub-chapterispresentedintablebelow.

Table4-2Relevantliterature

Reference Comment

(Blume,Easley,&O'Hara,1994)

Investigationoftheinformationalroleofvolumeanditsapplicabilityfortechnicalanalysis

(Sarr&Lybek,2002) Qualitativeandquantitativeliquiditymeasuresappliedtoforeignexchange,money,bond,andequitymarkets

(Spodniak,Collan,&Viljainen,2015)

Descriptiveliquiditymeasures(volume,tradinghorizons,etc.)appliedtoEPADmarket

4.2.1 Tradinghorizons

Tradinghorizon,understoodhereasaderivativesproductwithdifferenttimeframe/maturity,isnotameasureofefficiencyorliquidityperse.Thetradinghorizonshowsfordifferentlistedcontractswhichmaturitiesthatcanbetradedandclearedandisthusanindicatorofhedging

possibilities.Inadditiontobiddingareasegmentation,tradinghorizonsprovideafundamentalcross-sectionaldivisionformostoftheefficiencyandliquiditymeasuresdiscussedhere.Byfocusingonindividualtradinghorizonsoverperiodoftimeandacrossspace(biddingzones)whenmeasuringtradedvolumesandopeninterest,greaterinsightsintomarketbehaviourandlevelsofmarketactivitycanbegained.

Thereisessentiallynoother‘task’ormethodherethansimplybeingawareofthecontracttimeframeswhencollectinginformationabouttradedvolumesandopeninterest.

4.2.2 Tradedvolumes

Ingeneral,tradedvolumes1,representingnumberofMWhsoldandboughtforgivenderivativeduringaspecifiedperiod,provideinformationonliquidityanddemandforaparticularhedginginstrument.Contractsinhighdemandaretradedmoreandcanbeeasilysoldorboughtwhereascontractswithlowtradedvolumescanbedifficulttosellorbuy.

Thismeasureistraditionallyusedtomeasuretheexistenceoflargenumberoftransactionsandmarketparticipants.Hence,tradingvolumeismostlylinkedtomarketbreadth,i.e.ordersarenumerousandlargeinvolumewithminimalimpactonprices.Relatingthetradedvolumeswithpricesforthesetrades,wecancalculateturnover(Eurovolume),seeEquation11wherePiandQiareindividualtradesforderivativeiduringagiventimeperiod.

𝑉G = 𝑃G𝑄G(11)

Acomplementarymeasureformarketbreadthcanbecalculatedbydividingthetradedvolume(Qi)withthenumberoftransactions,whichgivestheaveragetradesize.Largeaveragetradesizeindicatestheexistenceofnumerousandlargetrades.Smallaveragesizeindicatesthatthecontractismoreusedforadaptionofaportfoliothanforspeculativetrading.

Toallowforgreaterdetailintheanalyses,tradingvolumesforeachproductshouldbestructuredalongtradinghorizonsandbiddingzonesoveranumberoftimeperiods,suchasyearsandmonths.Additionalgranularitymaybegainedbydisentanglingtradedvolumesbymarketplace,suchasover-the-counterandexchange.Suchdatastructuringprovidesaglanceintoliquidityandquickoverviewofthemarketstructure;whichproductsarebeingmosttraded,inwhichbiddingareas,forwhatmaturity,andatwhichmarketplace2.

1TradedvolumesaresimplytheQiinEquation11.2Alinkbetweentradedvolumesandmarketefficiencyhasbeendiscussed(Antoniou,Ergul,Holmes,&Priestley,1997;Blume,Easley,&O'Hara,1994).Ifthesefindingsweretranslatedinto

4.2.3 Openinterest

Openinterestreferstoallopenpositionswithaclearinghouseatagivenpointintime.Itcorrespondstothetotalamountofenergyinderivativescontractsthathavenotyetbeenclosedoutbyanoffsettingtrade,fulfilledbymeansofthephysicaldeliveryoftheunderlyingassetorexecutedviacashsettlement.Animportantmetrictounderstandfinancialmarketsisthedevelopmentofopeninterest.Whenacontractisboughtorsoldforhedgingpurposes,theintentionistokeepthenewpositionuntilthecontractgoestodelivery.Ifthecontractisbought(sold)fortradingpurposes,theideaismostoftentosell(buy)asimilarcontractforahigher(lower)priceatalaterpointintime.Thefirstofthetrader’stransactionwillincreaseopeninterest,whilethesecondwillreduceopeninterest.Hence,thesizeoftheopeninterestinacontractinrelationtothetradedvolumesinthecontractshowstowhatextentthecontractisusedprimarilyforhedgingpurposesorfortrading.

Openinterestisamoredynamicmeasureofliquiditycomparedtoe.g.tradedvolumes,becauseitreflectsthedecreaseorincreaseofmoneybroughtintothefuturesmarket.Openinterestofindividualcontractsinmostfuturesmarketstypicallyfollowsapatternrepresentedbylowvalueswhendeliveryperiodisdistant,followedbyapeakrelativelyclosetodelivery,andthenafallwhenthedeliveryperiodapproaches(Williams,Peck,Park,&Rozelle,1998).Electricitycontractsusedforhedgingare,however,normallykeptuntildelivery.ThedropsjustaheadofdeliveryseeninFigure4-1representthecascadingeffect(yearlycontractsturnedintoquarterlycontractsbeforeyearend,etc.),butthetotalopeninterestisfairlystable.

Similarmeasureofliquidityasopeninterestischurnrate,whichisaratiobetweenthetotaltradedvolumes(Qi)ofpowerderivativeiandthetotalelectricityconsumption(Vi)inagivenperiod,seeEquation12.Churnratecanbeunderstoodasanumbershowinghowmanytimesamegawatthouristradedbeforeitisdeliveredtothefinalconsumer.

𝐶𝑅G = 𝑄G𝑉G

Churnratemightbeagoodindicatoroftradingsignificance,butitislessrelevantasanindicatorofhedgingsignificance.Theactualtradedvolumeforaspecificbiddingzoneconsistsofboth

Nordicelectricityderivatives,pasttradingvolumes,inconjunctionwithpastreturns,wouldprovideusefulinformationinpredictingfuturereturns.Thetradingvolumewouldbemostlyrelevantforthinlytradedderivatives,suchasEPADs.Toevaluatetheproposedrelationship,amarketmodelshouldbeestimatedwherecurrentpowerderivativesreturnsaredependentonpastreturns,pastvolumesandmeasureofrisk.Ifthepastvolumeswouldsignificantlycontributetoprediction,trades/speculatorsusingsuchmeasurewouldbenefitfrombetterqualityinformationnotcontainedinpricesalone.Nonetheless,sincethemainpurposeofthisstudyiscontractliquidityinsteadofmarketefficiency,werecommendusingthetradedvolumemeasurefortheliquiditypurposeonly.

EPADsandSYScontractsaswellasday-aheadcontractsintheElspotmarket.However,‘splitting’theSYStradebetweenbiddingzoneswouldbecomplex(ifpossibleatall3)anddoesnotmakesense.

Thuswhilewefindopeninterestpercontractasvaluableinformationaboutthevariousbiddingzones,wecannotseehowchurnratescanbecalculatedandappliedbytheregulatorsinausefulway.

Figure4-1OpeninterestinSYSandEPADcontracts(Source:Nasdaq/ECGroup)

4.3 Pricemeasures

Pricemeasuresinthissectionrelatetothepricediscoveryprocessofdeterminingaderivative’spricethroughbuyerandsellerinteractioninthemarketplace.Therapiditywithwhichmarket

3Severalmarketparticipantshavephysicalpositionstohedgeinnumerousbiddingzonesanddonothavetospecifyforwhichzoneaparticulartradeismade.Infact,onetrademaybeintendedtohedgepositionsinnumerouszones.Marketparticipantswithoutphysicalpositionsmayalsotradewithoutanyregardforthezonalpricesorthezonalstructureatall.

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2013 2014 2015

Openinterest,SYS&EPADcontracts[TWh]

WeeksandDays Months Quarters Years Total

participantsreacttonewinformation,theirjudgementandthequalityofinformationallaffectthedynamicsofthepricediscoveryprocess.

Wediscussthreeexamplesofpricemeasuresforpowerderivativesassessedcross-sectionally(tradinghorizonsandbiddingzones)andacrosstime.Thefirstmeasureestimatesriskpremiumsasthefutures-spot-bias;thesecondevaluatestheimpactofilliquidityonderivativesprices/returns(Amihud,2002);andthethirdevaluatestheoveralllong-termandshort-termefficiencyofthederivativesandtheunderlyingprices.Seealsosection2.1forsometheoreticalperspectivestotheriskpremium.

Fortheregulators’analyses,wesuggestrelyingontheriskpremiumanalysisdescribedinsection4.3.1.1

Table4-3Relevantliteratureforpricemeasures

Reference Comment

(Bessembinder&Lemmon,2002)

Negativerelationshipofspotpricevarianceandpositiverelationshipofspotpriceskewnesstoriskpremiums

(Marckhoff&Wimschulte,2009)

Ex-postriskpremiumsforCfDs(EPADs)calculatedfor2001-2006,includingconfirmationofBessembinder&Lemmon(2002)model

(Spodniak,Chernenko,&Nilsson,2014)

Ex-postriskpremiumsforEPADs2001-2013

(Redl,Haas,Huber,&Böhm,2009)

PriceformationoffuturesandforwardcontractsonEEXandNordPool,includingex-postriskpremiumsforNov2003-May2008

4.3.1 Riskpremium

Oneapproachtoinvestigatepricingaccuracyofpowerderivativescontractsistocalculateriskpremiums,whicharesystematicdifferencesbetweenthetradingpricesofanelectricitycontract(FK,L)andthecontract’sexpected(ex-ante)spotpricewhenitisdelivered(EK(SL,L)).Wecallthissystematicdifferenceforwardriskpremium(Benth&Meyer-Brandis,2009;Longstaff&Wang,2004;Benth,Cartea,&Kiesel,2008;Marckhoff&Wimschulte,2009).Forwardriskpremiumscanbeunderstoodasmark-upsorcompensationsinthederivativescontractschargedeitherbytraders,suppliersorconsumersforbearingthepriceriskfortheunderlyingcommodity(Longstaff&Wang,2004,p.1887).

Theunderlyingquestionbehindriskpremiumsiswhethertheydenoteanaturalbehaviourofrisk-aversemarketparticipantswillingtopay(accept)ariskpremium(discount)fortransferringtheriskofunfavourablespotpricemovements(Marckhoff&Wimschulte,2009),orwhetherthey

areasignofmarketinefficiency,suchasarbitrage(Borenstein,Bushnell,Knittel,&Wolfram,2008).Fromtheavailabledataandempiricalanalysiswecannotdisentanglethetwodirectly,butwecanstudythemagnitudes,persistency,direction,andsignificanceofriskpremiums,whichthenshedlightontheaccuracyofthemarkettopricepowerderivatives.Putdifferently,bystudyingriskpremiumswemayassess,whetherthespecificpowerderivativescontractsareunbiasedpredictorsofthefuturespotprice.

4.3.1.1 Ex-postriskpremium

Intheforwardandfuturespricingliteratureitisacommonpracticetocalculatetheex-antepremiumintheforwardpriceastheex-postdifferentialbetweenthefuturespricesandtherealizeddeliverydatespotprices(Redl,Haas,Huber,&Böhm,2009).LongstaffandWang(2004)suggestedthisex-postapproachtoriskpremiumsinelectricityforwardpricesbyusing𝑆M,Masaproxyfor𝐸"(𝑆M,M)),andMarckhoffandWimschulte(2009)appliedthisproxytocalculatetheex-postriskpremiumforEPADs.Ex-postriskpremiumsareeasytocalculatewithreadilyavailabledata,whiletheex-anteapproachreliesonunobservableinformation(theexpectedprices).

ForwardriskpremiuminaderivativescontractattimetfordeliveryattimeTisequaltothederivativespriceFt,TattimetfordeliveryattimeTminustheaveragerealizedspotpriceST,TbetweenthebeginningandendofthedeliveryperiodT1andT2respectively.Theex-anteriskpremiumisexpressedbyEquation13andtheex-postriskpremiumisexpressedbyEquation14:

𝜋",M = 𝐹",M − 𝐸"(𝑆M,M) (13)

𝜋",M = 𝐹",M −1𝑛

𝑆M,M

ThederivativespriceFt,Tcanbeforanytypeofpowerderivativescontract,suchassystempricefuturesorEPAD.Forclarity,theex-postriskpremiumcalculationforEPADsisshowninEquation15,where𝐸𝑃𝐴𝐷",MrepresentstheEPAD’spriceattimetfordeliveryattimeT.Theriskpremiumisthispriceminustheaveragerealizedspotdifferencebetweenthezonalprice𝑃SXYZ[andthesystemprice𝑆S

\]^"Z_betweenthebeginningandendofthedeliveryperiodT1andT2,respectively.

𝜋",M`aXb = 𝐸𝑃𝐴𝐷",M −1𝑛

(𝑃SXYZ[ − 𝑆S\]^"Z_)

Fortheregulators’analysis,wesuggestusingthelastrecordedtradingprice𝐸𝑃𝐴𝐷",M(orFt,TforSYScontractsorlocalcontractsfore.g.Germany)forindividualcontractsinthecalculations

becauseitrepresentsthebestestimateoftheexpectedpricejustbeforedeliverystarts.Riskpremiumscanbecalculatedforindividualcontracts(e.g.monthlyStockholmEPADs,baseyearfutures,etc.)bytakingthedifferencebetweenthelasttradingdaypriceofaderivativeandtheaveragespotoutcomeduringtheunderlyingdeliveryperiod.Riskpremiumscalculatedforindividualcontractscanthenbepresentedinyearlyaveragesoverindividualtradinghorizons(yearly,quarterlyormonthly)andbiddingareas.

Notethatcontractswithshortertradinghorizon/maturityandclosesttodelivery,suchasdaily,weekly,andmonthly,willtypicallycontainthelowestforecasterrorsmadebymarketparticipants.Nonetheless,riskpremiumsforlongermaturities,suchasyearlycontracts,canbealsocalculatedwhilenotingthatmarketparticipantscanmakegreaterforecastingerrorsforlongercontractsorcontractsfurtherawayfromdelivery(e.g.monthlycontractmaturingthreemonthsfromnow).

Statisticalsignificanceofthequantifiedriskpremiumshouldalsobetestedbythet-teststatistic,i.e.testwhethertheriskpremiumsaredifferentfromzerounderagivenlevelofsignificance.Theformulaforone-samplet-testisexpressedinEquation16,where𝑥isthemeanriskpremiuminthesample,sisthestandarddeviationofriskpremiuminthesample,nisthesamplesize,and𝜇disthehypothesizedpopulationmean(e.g.zero).Thesamplecanbeallex-postriskpremiumscalculatedforeachderivativeclass,suchasmonthlyEPADs,inagivenbiddingzoneoverayear,forinstance.Soifweuseonlyfront-monthEPADs(monthlyEPADwithnextmonthdelivery)thesamplesizeoveroneyearwouldbetwelve.Foryearlyderivativesandwhenusingonlyfront-yearcontracts(yearlyderivativewithnextyeardelivery)wewouldneedtoapplythet-testonatleastafour-yearperiod,i.e.thesamplesizewouldbefour(atleast)becausethereisonlyoneriskpremiumperyearforyearlycontractsaccordingtotheoutlinedmethodology4.

𝑡 = 𝑥 − 𝜇d𝑠

TheT-testshowswhetherthesampleandpopulationmeanaredifferentornot.Ifthesampledriskpremiumisnotsignificantlydifferentfromzero,thereisnosystematicbiasinthederivativespricescomparedtotheunderlyingspotprices.Evenwhenstatisticalsignificanceofriskpremiumisconfirmedat5%orlower,themagnitudes,signs,andtechno-economicreasonsbehindtheseshouldbeexploredbeforemakinginterpretativeconclusions.

4Analternativemethodologyistocalculatetheex-postpremiumsondailybasisinsteadofaveragingovertheentiredeliveryperiod,see(Marckhoff&Wimschulte,2009),whichwouldprovidee.g.365riskpremiumsforyearlyderivativeoverayear,sot-testcanbedirectlyappliedonyearlyderivativesoverayear.However,foroperationalsimplicity,werecommendthesimplerapproachdescribedaboveofjustcomparingthelasttradingdaypriceforaderivativeandtheaverageex-postspotoutcomes.

Insummary,werecommendcalculatingaverageex-postriskpremiumsforindividualcontractsandtestingtheirstatisticalsignificance.Comparativeinsightsonriskpremiummagnitudes,directions,andsignificancewillbegainedwhichwouldexposepossiblesystematicbiasesofderivatives.

4.3.1.2 Ex-postpercentageriskpremium

Forwardriskpremiumscanalsobeexpressedaspercentageofthespotpriceatdelivery.Redletal.(2009)callthismeasurethefutures-spot-bias.Usingthedefinitionsdescribedintheprevioussection,thepercentageriskpremiumcanbeexpressedas:

ΔM = 𝐹",M − 𝑆M,M

𝑆M,M

ΔListherelativedifferencebetweenthederivativesandspotprice,FK,ListheaverageofaderivativescontracttradedinperiodtforthedeliveryinT,andSL,Listheaverageunderlyingspotpriceduringthedeliveryperiod.Similarlyasabove,thismeasurecouldbecalculatednotonlyontheaveragesofentiredeliveryperiodbutalsoondailybasis.

Thisratiomeasuresriskpremiumsasapercentageofthespotpricesinthedeliveryperiod.Statisticalsignificanceofthequantifiedriskpremiumscanbetestedbythet-teststatistic.Theinterpretationishowmanypercentagepointsabove(+%)orbelow(-%)aderivativescontractwastradedwithrespecttospotpricesinthedeliveryperiod.Thepercentagevaluesmayeasetheinterpretationofriskpremiums,especiallyacrossdifferentbiddingareas,buttheymightalsoconfuse,aslargepercentagevaluescouldbedrivenbysmallorzeroday-aheadzonalspreadatdelivery(SL,L)inthedenominator.Thuswedonotrecommendusingarelativemeasureofriskpremiums.

4.3.1.3 Riskpremiummatrix

Riskpremiumsarelikelytovaryovertime,duetocontinuouslychangingmarketconditions.Toeasetheinterpretationofriskpremiums,weproceedwithadiscussionondeterminantsanddynamicsofriskpremiums.

Itcanbeproposedthattheinteractionbetweenstructuralmarketshares(Kristiansen,2004)withriskaversionhasthepotentialtoexplainboththenegativeterm-structureandpositiveterm-structureofriskpremiums.Bystructuralmarketsharewemeantheshareofdemand(consumers)andsupply(producers)inthehedgingposition.Figure4-2depictstheproposedrelationshipinasimplexychartwithfourhighlightedsectors,wheretheverticalaxisrepresentstheriskaversiondimensionandhorizontalaxisthemarketsharedimension.Thefigureexplains

thesignandmagnitudeofriskpremiumsintheelectricityfuturescontractsbyfocusingonfoursectorsinthechart.

Figure4-2Explanationofsignandmagnitudeofforwardriskpremiumsaccordingtoriskaversionandmarketsharedimensions (Source:Spodniak,P.(2017))

Thecurrenttheorygenerallypredictsanegativetermstructureofriskpremiums,i.e.movingfromthebottom-righttothetop-leftcornerormoregenerallyfromthebottom-halftotheupper-halfofthediagramduringthedecreasingtimetomaturity.Thisisexplainedbysmallernumberofconsumershedginglonger-termpositionscombinedwithhighriskaversionofproducerseagertohedgetheirlong-termprofits(bottom-rightsector).Thisisalsocalledmarketpowerofconsumerswhopushthefuturespricesbelowtheirexpecteddeliveryprice(strictlynegativeriskpremium).Whencomingclosertothecontractdeliverymoreconsumersenterhedgingpositionsbecauseofincreasingdesiretohedgeagainstshort-termrisks(top-leftsector).Thissituationiscalledmarketpowerofproducerswhocanchargeapremiumonthefuturescontractcomparedtotheexpecteddeliverydateprice(strictlypositiveriskpremium).

Riskaversionandmarketsharesarebothinfluencedbymanyfundamentalfactors,suchasexceptionallycoldorwarmweather,peak/offpeakperiods,high/lowhydroreservoirinflows,CO2prices,etc.(Redl,Haas,Huber,&Böhm,2009;Redl&Bunn,2013).However,mostofthepasttheoreticalandempiricalstudieshaveworkedwiththe“traditional”electricitysystemdominatedbydispatchablegenerationandinelasticdemand.Thisishardlythecaseanymore.Duetochangingelasticityorflexibilityofelectricitysupplyanddemandwecanexpectchangingdynamics(directionandmagnitude)oftheforwardriskpremium.Thuswecannottakeitforgrantedthatforwardriskpremiumsfollowthenegativetermstructure,andhencesystematicallypositiveandnegativetermstructurescanbeobserved.

4.3.2 Amihud

Amihud(2002)showsthatacrossstocksandovertime,expectedstockreturnsareanincreasingfunctionofexpectedilliquidity.Hedefinesacross-sectionrelationshipbetweenilliquidityandstockreturnas:

𝐼𝐿𝐿𝐼𝑄G] = 1/𝐷G] 𝑅G]i /𝑉𝑂𝐿𝐿𝐷Gk]ibG]

𝐼𝐿𝐿𝐼𝑄G]istheilliquidityratioforstockiinyeary

𝐷G]isthenumberofdaysforwhichdataareavailableforstockiinyeary

𝑅G]iisthereturnonstockiondaydofyeary

𝑉𝑂𝐿𝐿𝐷Gk]iistherespectivedailyvolumeindollars

𝑅G]i /𝑉𝑂𝐿𝐿𝐷Gk]iisaverageratioofthedailyabsolutereturntothe(dollar)tradingvolumeonthatday

ILLIQisaratiogivingtheabsolute(percentage)pricechangeperdollarofdailytradingvolume,orthedailypriceimpactoftheorderflow.Thepositiveeffectofilliquidityonstockreturnsisthenmodelledbycross-sectionalestimationofmonthlystockreturnsonmultipleriskandotherrelevantvariables.Theproposedrelationshipisthatthegreatertheilliquidityofasecuritythegreatertheexpectedreturn,aftercontrollingforriskandotherrelevantmeasures(stockcharacteristics,dividendyield,etc.).

TheempiricalandtheoreticalapplicationofAmihudmeasureforelectricityderivativesmarketsseemsratherlimited.Inordertocorrectlyspecifyacross-sectionalmodelforpowerderivativesreturns,relevantmeasureshavetobefirstspecified.Suchmeasuresmayincludegenerationanddemandstructure,pricevolatility,hydrosituation,tradedvolumes,etc.Afterrelevantvariablesareidentified,cross-sectionregressionofpowerderivativesreturnonilliquiditymaybeestimated.

WedonotrecommendusingtheAmihudmeasureforthetaskofmeasuringilliquiditynowbecauseofthelackingempiricalevidencefromcommodity/electricitymarkets.

4.3.3 Long-termandshort-termmarketefficiency

Acompletelydifferentapproachtomeasurepriceformationistotesttheefficientmarkethypothesisandstudythepricediscoveryprocessesoffuturespricesandexpectedspotprices(Growitsch&Nepal,2009;Ballester,Climent,&Furió,2016;Redl,Haas,Huber,&Böhm,2009).Methodologically,thesestudiesrelymainlyoneconometrictechniques.Namely,cointegrationisusedfortestingtheefficientmarkethypothesis(long-runefficiency),andvectorerrorcorrectionmodels(VECM)areusedforinformationtransferobservationsbetweenthefuturesandspotpriceseries(short-runefficiency).

Previousempiricalstudiesonmarketefficiencyincommoditiesmarketssuggestthatshort-termmarketsarenotasefficientaslong-termones(Kellard,Newbold,Rayner,&Ennew,1999;Wang&Ke,2005;SpodniakP.,2015).Bothlong-termandshorttermefficienciescanbetestedbyusingdailypricedataforderivativespricesandtheunderlyingspotpricesforeachcontractmaturity(daily,monthly,etc.)andbiddingzone.

Wedonotrecommendthisapproachfortheregulators’analysesnow.Despitetheanalyticalappealofthesetechniques,theyarecomputationallyintensiveandtheiroperationalimplementationislimited.However,themethoddescribesametricformarketefficiencyandcanbeusefulreferencetokeepinmind,andisincludedheremerelyforthatpurpose.Furthertechnicaldetailsinthefollowingstudies(Lai&Lai,1991;Growitsch&Nepal,2009;Redl,Haas,Huber,&Böhm,2009;SpodniakP.,2015).

Therearethreestepsinthisapproach:

1. TestforstationarityBeginwithtestingwhetherthepriceseriesisstationary,i.e.whetheritsstatisticalproperties(mean,variance,etc.)areconstantovertime.Thisisaninitialsteptoavoidproblemswithstatisticalinferencesinthenextsteps.StationaritypropertiesofdailyderivativespricesandtheunderlyingspotpricescanbetestedbyAugmentedDickeyFuller(ADF),Phillips-Perrontest(PP),andthestationaritytestofKwiatkowski–Phillips–

Schmidt–Shin(KPSS).Theunitroottests,ADFandPP,holdthenullhypothesisthatatimeseriesisI(1),whilethestationaritytest,KPSS,holdsthenullofI(0).Iftheoriginallynon-stationarypriceseriesarefoundtobestationaryafterfirst-orderdifferencing,i.e.integratedorder1denotedbyI(1)),proceedtothenextstep,otherwiseuseanothermetric.

2. Runcointegrationtest(long-runrelationship)Thehypothesisofmarketefficiencysuggeststhatderivativespricesdonotconsistentlyover-orunder-estimatethespotprices.Johansen’scointegrationapproachcanbeusedtotestwhetherlong-runequilibriumrelationshipexistsbetweenthespotandderivativesprices.Johansen’sprocedureisbasedonavectorautoregression(VAR)modelthatallowsforpossibleinteractionsinthedeterminationofspotpricesandderivativesprices.IfwefindthatSt(spotpriceattimet)andFt-1(futurespriceiperiodsbeforethecontractmaturesattimet)arecointegrated,wefindanecessaryconditionformarketefficiency(Lai&Lai,1991).Thecointegrationtestshouldberunonindividualcontractmaturities(e.g.monthly,quarterly,yearly)andacrossbiddingareasonrelativelylargesamples.Ifcointegratingrelationshipisnotfoundthiswouldmeanthatderivativespricesprovidelittleinformationabouttheunderlyingspotpricemovements.

3. Testtherestrictionsonthecointegratingparameters(short-runrelationship)Ifcointegratedrelationshiphasbeenfoundbetweenthepriceseriesinthepreviousstep,therealsoexistsacorrespondingerrorcorrectionrepresentationofthevariables.Vectorerrorcorrection(VEC)model(Engle&Granger,1987)canbeusedtostudythepriceadjustmentprocessofshort-rundeviationsfromthelong-runequilibrium.Insightsgainedfromthisexercisearedetailedobservationsonhowquickly(adjustmentspeed)andinwhichmarket(spotorderivatives)thecorrectiontolong-runequilibriumtakesplace.Itmaybefoundthatonemarketreactsmuchmorequickly/efficientlytonewinformationwhereasothermaybeweaklyexogenous(Wang&Ke,2005).Additionalhypothesisoffullpriceconvergenceofspotandderivativespricesinthelong-runcanbedonebyplacingarestrictiononthecointegratingparameter.

Reliablyestimatingthemeasuresdescribedhererequireslongertimeseriesdataonprices,carefulmodelspecification,andstatisticalsoftware.Suchanalysescouldalsobedoneseparatelyoncontractpricesoriginatingfromdifferentmarketplaces,suchasover-the-counter(OTC)vs.electronictradingsystem(ETS)toseewhetherdifferentmarketplacesprovidedifferentmarketefficiency.Nonetheless,computationalburdenmayoutweighthepotentialbenefitsofthesetechniques.

4.4 Transactioncostmeasures

Transactioncostshavepronouncedeffectsonthenetgainstoinvestmentsaswellasmarketequilibriumreturns,andthusalsoonhedgingdecisionsandhedgingefficiencyandeffectiveness.Transactioncostmeasurescapturethecostsoftradingafinancialassetandtypicallyincludeexplicitcosts(suchasbrokeragecommissionsandmembershipfees)andbid-askspreads.Tradingcostsaregenerallychallengingtoanalyseempiricallybecausetheyvarydependingonthesizeofatrade,firmortimeofyear,forinstance.Bid-askspreadsmayalsovaryacrosstradingplatforms,suchasorganizedexchangeandOTC,wheredifferencesin,forinstance,order-processingcostsandinformationqualitytranslateintorelativedifferencesinbid-askspreads.Inthissectionwediscusstwotransactioncostmeasures;theabsolutebid-askspread,andRoll’simplicitmeasureofeffectivebid-askspread.

Table4-4Relevantliteratureabouttransactioncostsmeasures

Reference Comment

(Chung,NessVan,&NessVan,2002)

Comparisonofexecutioncosts(spreads)anddifferencesindepthsbetweenNasdaqandNYSEstocks

(BessembinderH.,1999) Comparisonofexecutioncosts(spreads)betweenNasdaqandNYSEstocks

(Spodniak,Collan,&Viljainen,2015)

Comparisonofbid-askspreadsinabsoluteandpercentagevaluesforEPADcontracts2007-2014.

4.4.1 Quotedbid-askspread

Thequotedspreadisthedifferencebetweenamarketmaker'sbidandaskquotes.Thebestquotedbid-askspreadisthedifferencebetweenthehighestbidding(buying)priceandthelowestasking(selling)price.Thebid-askspreadisadirectmeasureofliquiditywithmorepronouncedeffectsontransactioncostsformarketparticipants.Thebid-askspreadreflectsi)order-processingcosts;ii)asymmetricinformationcosts;iii)inventory-carryingcosts;andiv)oligopolisticmarketstructurecosts(Sarr&Lybek,2002).Generally,thesmallerthebid-askspread,themoreliquidandpossiblyefficientthemarket.Conversely,largespreadscancausehighsearchanddelaycosts.Bid-askspreadsvarythroughouttime,contractmaturities,areas,tradingarena(OTCvs.exchange)anddependonthemarketparticipants’perceptionofrisks.

Whilemarketmakersgenerallycommitthemselvestoensurebid-askspreadsarewithinagreedlimits,theactualmarketspreadmayvarybothwithineachdayandovertime.Also,theremaybealargediscrepancybetweentheirquotesandthemarketparticipants’willingnesstopayoraccept,especiallywhenthemarketisverythin.

Whenassessingthebid-askspread,itisquiteimportanttoincludealltradingplatformsintheanalysis.Ifthetradingfrequencyislow,thespreadinoffersonexchangescreensmaybelarge,makingitbeneficialtoaskanOTCbrokerforassistanceinfindingthe‘real’bid-askspread.Ifthetradingfrequencyishighandthespreadinoffersonthescreenisverylow,thereisnobenefitfromtakingtimetoaskabrokerforassistance.Thisalsoexplainswhybrokerstendtohavesmallmarketsharesinveryliquidcontracts.

Tocalculateanaveragebid-askspread(𝐵𝐵𝑂G")foraderivativeiduringatimeperiodt,dividethesumofdifferencesbetweenthebestask𝐴G"andthebestbid𝐵G"priceforaderivativeiduringtimetbythenumberofrelevanttimeintervalsNinthesample,seeEquation19.

𝐵𝐵𝑂G" =(𝐴G" − 𝐵G")

Theaveragebid-askspreadisoftencalculatedfromdailyfrequencydatawhichwouldquotetheday’sbestbid(thehighestbuyingoffer)andtheday’sbestask(thelowestsellingoffer)amongotherdata,suchasvolumetradedornumberofcontractstraded.Averagebid-askspreadshouldbecalculatedforindividualcontracts,i.e.tradinghorizonandbiddingareafromexchangeorOTCdata.Theaveragescanalsobereportedonaggregatelevelforindividualbiddingzonesoverindividualyearsormonths.

Fortradingassessments,therelevanttimeintervalisoftenadayoranhourbutcanbeevenshorter.Forhedgingassessments,therelevanttimeintervalisoftenlongerthanadaysuchasaweekoramonth.Hedgingstrategiesdescribeoftenamonthlydevelopmentofhedgingpositions.However,forretailersthereisusuallyarequirementforback-to-backhedgingofthesystempriceifanewsubstantialfixedpricecontractisreceived,whiletherequirementforhedgingthezonalriskislessurgent.Thisisduetothefactthatthevolatility,measuredinEUR/MWh,issmallerforEPADsthanforSYScontracts.

InaccordancewiththeactualhedgingpracticesintheNordicmarket,thereareafewissuestoconsiderwhenassessingthebid-askspreadintheNordicmarket.

1. DataavailabilityEPADsaremostlytradedOTC.ThemarketshareforNasdaqisaround20%.Tradingbehaviouralsosuggeststhattherearebettersourcesforbid-askspreadsthanexchangedata.WesuggesttheregulatorsapproachthelargeOTCbrokersandexploretheopportunitiestoobtainbid-askstatisticsfromoneormoreofthem.Ifsuchdataaremadeavailabletotheregulators,thereisnoneedtoestimatethebid-askspreadbymeansofe.g.Roll’smeasure.

2. TimeresolutionTheEPADmarketisa‘slower’marketthantheSYSmarket.MarketparticipantsseemtotakeintoaccountthatgettingthecorrectlongorshortpositioninanEPADisnota

matterofsecondsorminutes.ThegenerallyhavetimeforanOTCbrokertosearchforabetterdealthantheoneimmediatelyavailableatNasdaq.Thisgenerallyimpliesthatthebestbidsandasksarenotnecessarilyavailableinstantaneously.Thusitisnotnecessarilythedailybid-askspreadthatistherelevantmeasureofthetransactioncost.Wesuggestaweeklyapproach,wherethebestbid-askspreadperweekisinterpretedastherelevantcost.

3. TimehorizonThebid-askspreadchangesovertime,andthusanaverageovertimemustbeapplied.Aswiththecorrelationanalyses,thereisabalancebetweenhavingsufficientobservationstocovertherealisticpossibleoutcomesandnotincludingpastobservationsthatbearsnorelevancefortheperiodsahead.Itseemsreasonabletoapplyaone-yeartimehorizonasthiswillinclude52weeklyobservations.

4. NothresholdsThereisgenerallynoacceptedlevelofbid-askspreadsthatisconsidered‘good’orefficient.Incompetitivemarkets,itseemsfairtoassumethatwhateverthebid-askspreadactuallyis,itisameasureofactualcostsandthusefficient,whereasinlesscompetitivemarkets,onemightsuspectthatwhateverthelevelofthebid-askspread,itisnotnecessarilyefficient.Whetherconsultingwithmarketparticipantscanreducethisinformationalproblemremainstobeseen.

4.4.2 Roll’smeasure

Roll’smeasureisamethodappliedinstockmarketresearchtoinfereffectivebid-askspreaddirectlyfromatimeseriesofmarketprices.Theeffectivespreaddiffersfromthequotedspreadoutlinedinsection4.4.1.Theeffectivespreadisthedifferencebetweenthepriceatwhichthemarketmaker/dealerbuys(sells)asecurityandthepriceatwhichheorshesubsequentlysells(buys)it(Smith&Whaley,1994).Sincequotedbid-askspreadsforpowerderivativescanbequiteeffectivelycollectedfromexchangesandsomeOTCbrokers,weassumethecostsinestimatingeffectivebid-askspreadsexceedsthepossiblebenefits.

Nonetheless,webrieflyoutlinethetechnicaldetailsandbackgroundofthismeasureasareferencepointforfutureanalysis.Roll(1984)estimatestheeffectivebid-askspreadsfromtheserialcovarianceofthechangesinprice.ThemeasureisspecifiedinEquation20:

S = 2 −Cov ΔP", ΔP"sl (20)

Thefirst-orderserialcovarianceinpricechangesisinverselyrelatedtotheeffectivebid-askspread.Thisimpliesthattheeffectivespreadcanbeinferredfromthesequenceofpricechangessimplybycomputingandtransformingtheserialcovariance.Twoassumptionsmusthold:1)the

assetistradedinaninformationallyefficientmarket,and2)theprobabilitydistributionofobservedpricechangesisstationary(atleastforshortintervals).Bothassumptionscanbetestedindependentlyortheyarethepartofthelong-termandshort-termmarketefficiencymeasuresdiscussedinsection4.3.3above.

4.5 Summaryofsuggestedefficiencymeasures

Thesuggestedsetofanalysescomprisesthreebroadandnon-exclusiveclassesofmeasuresthatareoperationalandcomputationallylessrestrictive.Theanalysesrelyondirectmarketdatawithouttheneedforestimating,modellingorforecastingcomplexsystems,whichinitselfwouldbearuncertainty.

Therecommendedliquiditymeasuresareallofthedescriptivemeasures,ex-postriskpremiumfromthepricemeasures,andbid-askspreadsfromthetransactioncostmeasures.Thedescriptivemeasures,namelytradedvolumesandopeninterestpartiallybutreliablyproxytheliquidityofacontract.Byusingthesemeasures,regulatorsgaininsightintothebreadthofthemarket(tradedvolumes)aswellwhethertheprimarypurposeofthecontractistradingorhedging(openinterest).

Werecommendcalculatingtheex-postriskpremiumasameasureofcontractefficiencybecausegreaterinsightonthemarketdynamicsbetweenbuyersandsellersofderivativescanbegained.Byobservingmagnitudes,directions,andsignificanceofex-postriskpremiumsacrosstradinghorizonsandbiddingareas,possiblesystematicbiasesinthepricingofderivativescanbeidentified.

Finally,bid-askspreadsobtainedeitherfromexchangesorOTCbrokerswillanswerthequestionsonthecostofhedgingaswellastheunderlyingliquidity.Themagnitudesofthequotedbid-askspreadswillrevealthetransactioncostsmarketparticipantsfacewhenparticipatinginthepowerderivativesmarkets.

Unfortunately,therearenoidentifiedthresholdsforthevariousmeasures.Thereisnoquickfixforthis,andthusaseparateobjectivefortheanalysesmustbetogainexperiencewiththeperformanceofthefinancialmarket.

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