12341–5236–7896510 9 30521 31 5 algorithmic trading in the...

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sveriges riksbank economic review 2013:1

* TheauthorswouldparticularlyliketothankSusannaGrufman,MiaHolmfeldt,KajKvaavik,AnnaLidberg,JennyMannent,KjellNordin,MattiasPersson,KasperRoszbachandJonasSöderberg.

AlgorithmictradingintheforeignexchangemarketMaria Bergsten and Johannes Forss sandahl*TheauthorsworkattheFinancialStabilityDepartmentoftheRiksbank.

The foreign exchange market is an important part of the financial system and performs

important functions for the real economy. Recently, trading in this market has become

increasingly automated as the use of electronic foreign exchange trading and algorithms

has increased. In this article, we analyse how and why algorithmic trading is used on

the market for Swedish krona. We also analyse how this trading affects the functioning

of the market. From interviews with market participants, we reach the conclusion that

algorithmic trading is a component of competition-driven technological development.

On the whole, it should therefore contribute towards a more efficient foreign exchange

market with lower transaction costs. At the same time, it may entail certain risks for both

individual market participants and the financial system as a whole. Finally, we observe

that the market itself has worked out a practice for the functioning of algorithmic trading

in the foreign exchange market.

1.AweLL-FuNcTioNiNGFoReiGNexcHANGeMARKeTiSiMPoRTANTFoRTHeecoNoMy

iNGeNeRAL

Theforeignexchangemarketplaysanimportantroleforthebasicfunctionsofthefinancial

system:mediatingpayments,convertingsavingsintofundingandmanagingrisks(Sveriges

Riksbank,2013).Forforeignexchangetradingtofunctionsmoothly,itisimportantthatthe

variousrisksinthetransactionchainaremanagedassecurelyandefficientlyaspossible,

fromthemomentoftradeuntilthetransactionissettled.inaddition,theremustbemany

buyersandsellers,sothatcurrenciescanbesoldandboughtrapidly,whichistosaythat

marketliquidityisgood.

Afurtherconditionforanefficientmarketisthatthosetradingonithaveconfidence

initswayofworking.However,itdoeshappenonthefinancialmarketsthatinformation

onbothmarketparticipantsandfinancialinstrumentsisdeficientandunevenlyallocated,

whichcanhaveanegativeeffectonconfidence.iftheparticipants’confidenceinthe

functionalityofthemarketsdeclines,theirwillingnesstotradewitheachothermayalso

decline,makingitmoredifficulttorapidlybuyandsellfinancialinstruments.Amongother

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consequences,thismayaffecttheabilityofbanksandcompaniestomanagetheirrisksand

obtainfundingonthecapitalmarket.

Algorithmictradingispresentlyanormalwayoftradingonthefinancialmarketsand

involvesautomatedtradinginwhichordersandexecutionsarehandledbycomputers.it

isasub-categoryofelectronictrading,whichistradingviaanelectronictradingplatform.

Algorithmictradingincludeswhatisusuallyreferredtoashighfrequencytrading.High

frequencytradingisthusasub-categoryofalgorithmictradingandinvolvesplacingor

executingordersataveryhighfrequency.Theaimistogenerateprofitthroughthe

speedoftradingandtheinformationaladvantagecreatedbythetechnologyoverother

participantsonthemarket.

Themediaandacademicstudieshaveprimarilyfocusedonalgorithmictradingonthe

stockmarket.Thesediscussionsweregivenparticularimpetusbythetemporaryfallin

stockpricesof6May2010.onthisday,theuSequityindexDowJonesfellby9percent

withinthespaceofaboutfiveminutesbeforereturningtolargelythesamelevelaspriorto

thefallafewminuteslater.AccordingtoinvestigationsbytheuSauthorities,thisshort-

termcrash(alsocalledthe’flashcrash’)wascausedbyahedgefundthathadsoldavery

largeblockofindexfutures1throughacomputerprogrammedwithalgorithms,which

alsocreatedpressuretosellonothermarketsandforotherinstruments(u.S.commodity

FuturesTradingcommissionandtheu.S.Securitiesandexchangecommission,2010).

According,amongothers,toKirilenkoetal.(2011)highfrequencytradersalsocontributed

tothefallinstockprices.

inthesubsequentdiscussionsofalgorithmictrading–andhighfrequencytradingin

particular–thefocushasbeenonthepossibleeffectsonandrisksforthestockmarket’s

functioning,amongotherareas.Haldane(2011)consideredthatthenewcomputerised

tradingmayentail’fattertails’onthefinancialmarkets,whichistosaygreaterprobabilities

ofmajorfluctuationsinmarketprices.ioSco(2011)describedalgorithmictradingand

highfrequencytradingonthestockmarketandpointedouttheriskswiththeseformsof

trading.

However,relativelylittleattentionhasbeenfocusedontheforeignexchangemarket,

wherealgorithmictradingalsooccurs.Theforeignexchangemarketismuchlargerthan

thestockmarket(seechart1).Duringthetimeperiodinchart1,theRiksbank’smonetary

policycounterpartiesandcounterpartiesinforeignexchangetransactionshadadaily

turnoverofaboutSeK72billionontheforeignexchangemarketforSwedishkrona.2This

canbecomparedwithaboutSeK14billion,whichwasthedailyturnoverfortheStockholm

Stockexchange’s30largeststocks.

1 Afutureisabindingagreementbetweentwopartiestobuyorsellanunderlyingassetatacertainpriceatagivenpointintime.

2 SverigesRiksbank’sSeLMAstatistics,www.riksbank.se.

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0

50

100

150

200

250

300

Oct-05 Oct-06 Oct-07 Oct-08 Oct-09 Oct-10 Oct-11 Oct-12

Foreign exchange market, SEK Stock market, OMXS30

Chart 1. Daily turnover on the foreign exchange and stock markets, spotSEK billion

Sources: Reuters, EcoWin and the Riksbank.

Theforeignexchangemarketanditsfunctioningaresignificantforthesafeandefficient

functioningofthepaymentssystem,whichisoneoftheRiksbank’sobjectives.

consequently,itisinterestingtostudyhowalgorithmictradingaffectstheforeign

exchangemarket’sfunctioning.inthisarticle,weanalysehowandwhyalgorithmictrading

isusedontheforeignexchangemarketforSwedishkronaandhowitaffectsthe

functioningofthemarket.unlessstatedotherwise,inthisarticle,‘foreignexchange

market’refersexclusivelytothespotmarketforcurrencies.

FromtheRiksbank’spointofview,itisparticularlyinterestingtoknowwhether

algorithmictradingtakesplaceintradingwithSwedishkrona.consequently,wehave

interviewedsevenmarketparticipantswhoareactive,invariousways,ontheforeign

exchangemarketandintradingwithSwedishkrona.Theinterviewedparticipantsinclude

Swedishandforeignbanks,pensionfundmanagers,hedgefundsandnon-financial

companies.Thebanksincludedareresponsibleforabout50percentofturnoveronthe

foreignexchangemarketforSwedishkrona.3

weopenthearticlebydescribingafewcharacteristicsoftheforeignexchangemarket.

inaddition,wepresentthedifferentfunctionsofalgorithms,whichwedivideintofour

categories.wethengoontoanalysebothconceivablereasonsfortheuseofalgorithmic

tradingandtheriskswehaveidentifiedinouranalysis.Finally,weobservethatthemarket

itselfhasworkedoutapracticeforthefunctioningofthealgorithmictradingintheforeign

exchangemarket.

3 SverigesRiksbank’sSeLMAstatistics,www.riksbank.se.

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2.THeSTRucTuReoFTHeFoReiGNexcHANGeMARKeT

Theforeignexchangemarketisworldwideandisopenaroundtheclock.itscharacteristics

includetradingwithlargeamounts,alargenumberofparticipantsandtherapid

disseminationofpriceinformation.Theglobalturnoverinthismarketeverydayinvolves

amountscorrespondingtotensofthousandsofbillionsofSwedishkrona.4Theforeign

exchangetradingcanbedividedintotwosegments,tradingbetweenbanks(interbank)

andtradingbetweenbanksandtheircustomers.

Market makers have a central function on the foreign exchange market

currenciesaretradedoverthecounter(oTc),meaningthattradingdoesnottakeplaceon

aregulatedmarket.Tradingontheforeignexchangemarketusuallytakesplacethrough

whatareknownasmarketmakers.Amarketmakerisabankthatundertakestoquotebid

andaskpricesandtoguaranteethatitispossibletobuyandsellaminimumvolumein

oneorseveralcurrencypairs.inthisarticle,’marketmaker’referstobankswithformaland

informalcommitmentstoquotepricesinvariouscurrencypairs.

Foreignexchangetradingentailsrisksforthemarketmaker,forwhichthemarketmaker

compensatesitselfbyquotingthebidandaskpricessothatthedifferenceintheseistothe

marketmaker’sadvantage.Themarketmakerisvulnerabletoliquidityrisk,asitisforcedto

matchordersandinterestonthemarket.Liquidityriskistheriskofbeingaffectedbyaloss

asaresultoftherenotbeingenoughliquidityonthemarket.Poorliquiditymeansthatitis

difficulttofindbuyerswhenonewishestosellandvice-versa.

Themarketmakermayalsobevulnerabletomarketrisk,asthevalueofthepositiona

transactiongivesrisetomayvaryovertimeifthemarketmakerdoesnotenteranopposite

position.Marketriskistheriskthatfluctuationsinmarketpriceswillchangethemarket

valueofassetsandliabilitiesnegatively.

inaddition,themarketmakerisvulnerabletocreditriskwithregardtothecounterparty

untilthetransactionhasbeensettled.creditriskistheriskthatacounterpartyina

transactionwilllosetheabilitytorepayitsdebts.Thisriskcanbemitigatedbyestablishing

limitstorestrictexposuretoaparticularcounterparty.inforeignexchangetrading–andall

tradinginfinancialinstruments–creditrisksarisebut,inthiscontext,theseareknownas

counterpartyrisksandsettlementrisks.

The counterparty risk in foreign exchange (spot) trading is limited

Thecounterpartyriskinaforeignexchangetransaction(sometimesknownasreplacement

costrisk)istheriskthatthecounterpartywillfailonitsdebtsandthatthecurrencywill

consequentlyhavetobeboughtorsoldanewforanotherprice.counterpartyriskislimited

forspottransactions,asthetimebetweendateoftradeandsettlementissoshort,only2-3

days.undernormalmarketconditions,pricefluctuationsandcounterpartyriskareminimal,

4 SeealsoKingetal.(2011)foracomprehensivesurveyoftradingontheforeignexchangemarket.

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butduringcrisestheriskcanbegreaterasexchangeratescanfluctuatemore.while

counterpartyriskisoftendeemedtobesmall,settlementriskishigher.

oncertainfinancialmarkets,counterpartyriskisrestrictedbyacentralcounterparty

(ccP).5AccPactsasanintermediarybetweenthebuyerandsellerinthemanagement

ofasecuritiestransaction.Theoriginalcontractbetweenthebuyerandtheselleristhen

replacedbytwocontractswiththeccP.Thismeansthattheoriginalcounterpartiesinthe

transactionarenolongerexposedtoriskinrelationtoeachotherbutinsteadinrelationto

theccP.ontheforeignexchangemarketatpresent,thereisnoccPthatclearsforeign

exchangetransactionsinSwedishkrona.consequently,neitheristhereanypossibilityof

restrictingcounterpartyriskbytradingviasuchacounterparty.

The settlement risk in foreign exchange trading can be eliminated through CLS

Settlementriskcanbeeliminatedbysettlingforeignexchangetransactionsthroughthe

systemcontinuousLinkedSettlement(cLS).AllpaymentsincLSaresettledaccording

totheprincipleofpaymentversuspayment.Thisisachievedbythemembersmaking

paymentstoandreceivingpaymentsfromcLSaccounts–oneforeachcurrency–with

bothstagesoftheforeignexchangetransactionbeingsettledthroughtheseaccounts

simultaneously.onJanuary2013,cLSsettlestradesin17currencies,includingtheSwedish

krona.Statisticsfromthefirstsixmonthsof2012showthatabout90percentofall

foreignexchangetransactionsmadebythefourmajorSwedishbanksweresettledviacLS.

However,theproportionoftransactionssettledviacLSvariesbetweenthebanks.

There are different types of trading platforms on the foreign exchange market

Foreignexchangetradingtakesplaceeitherbytelephoneandchatorelectronicallyvia

tradingplatforms.Allofthetradingplatformsmediatecontactbetweenthebuyerand

theseller,andprovideinformationoncurrentpricesforvariouscurrencypairs.Accessto

informationondetailsineachcurrencyorder–forexampletheorderdepth–ismuchmore

limitedontheforeignexchangemarketthanonmarketplacesonthestockmarket.even

ifeachpricesetbyamarketmakeronlyappliestoaspecifiedordervolumeatacertain

pointintime,abuyerorasellercannotknowexactlythesizeoftheordervolumebehind

theprice.Thismeans,ononehand,thatitismoredifficulttocarryoutspeculativeforeign

exchangetradingonthebasisoftheavailableinformationonordervolumesoneachside

ofthemarketpricethanitisinstockexchangetrading.6ontheotherhand,itmeans

lowertransparency(comparedwiththestockmarket).Ahighleveloftransparencyis

fundamentallyimportantforthemaintenanceoflong-termconfidenceinfinancialmarkets.

5 ccPsareregulatedbytheeuregulationeMiR(theeuropeanMarketinfrastructureRegulation)onoTcderivatives,centralcounterpartiesandtraderepositories,whichcameintoforceon16August2012.

6 itshouldbenotedthathiddenliquidityalsooccursinstockmarkettrading,inwhatareknownas’darkpools’.

– 6 –


Tradingplatformscanbedividedintothreedifferenttypes:

• Inter-dealer electronic broking platforms.Theseplatformsweredevelopedinthe

1990sandareregarded,accordingtotheBankforinternationalSettlements(BiS,

2010),asthedominantsourceofinterbankliquidityontheforeignexchangemarket.

Theymediateinformationonvariousmarketmakers’indicativeprices.eBSand

Reuters,basedinLondon,arethetwodominantplatformswithinthiscategory.

• Multi-bank platforms. Theseplatformsarealsoknownasmulti-bankecNs

(electroniccommunicationnetworks).Theywerecreatedinthefirstdecadeofthis

centuryandresemblethepreviouscategoryinthattheymediateseveralmarket

makers’prices.onedifferenceisthattheyhavefreeraccessregulationsformarket

makers,whichmakesiteasierformarketmakerstojointheseplatforms.Another

differenceisthattheyarelargelyusedoutsidetheinterbankmarket,whichisto

saybymarketparticipantsthatarenotbanks.TheuSplatformsFxAll,currenex,

HotspotFx,StateStreetandFxconnectareexamplesofthistypeoftrading

platform.Therearealsoplatformsthatprovidestandardisedalgorithmictrading

functionsasaservice.currenexisonesuchplatform.

• Single-bank platforms.Thistypeofplatformisrunbyanindividualbank.The

platformmediatesonlytheindividualbank’sownpricesforvariouscurrencypairs,

unlikethetradingplatformsdiscussedabove,whichmediateseveralmarketmakers’

prices.inSweden,SeBhasaplatformofthistype,SeBTradingStation.other

examplesofbankswithsuchplatformsareJPMorgan,DeutscheBankandcitibank.

Aparticipantontheforeignexchangemarketcaneitherbedirectlyconnectedtoaplatform

orindirectlyconnectedviawhatisknownasaprimebroker.Abankthatisaprimebroker

allowscustomerstotradeontheforeignexchangemarketinthatbank’sname.Thismeans

thatthebankalsotakescreditriskexposurestothecustomerstradinginthismanner.

3.DiFFeReNTPuRPoSeSFoRALGoRiTHMSoNTHeFoReiGNexcHANGeMARKeT

Severalearlierstudieshaveobservedthatalgorithmictradingexistsontheforeign

exchangemarket.TheBiS(2011)claimsthathighfrequencytradingismostwidespreadin

tradinginthelargestandmostliquidcurrencypairssuchaseuR/uSD,GBP/uSDand

uSD/JPy,butthatitcouldspreadtotradinginlessliquidcurrencypairs.Kingetal.(2011)

alsodrawtheconclusionthathighfrequencytradingisresponsibleforalargeshareof

turnoverinthelargestandmostliquidcurrencypairs.

Themarketparticipantsweinterviewedinourstudyestimatethatalgorithmictrading

constitutes0-40percentoftradingincurrencypairsinwhichtheSwedishkronaisone

ofthecurrencies,and0-75percentoftradinginothercurrencypairs.Theseproportions

areassessedtobethehighestamongmarketmakers(20and39percentrespectively),

whiletheyareassessedtobesignificantlylowerbyotherparticipants(4and2percent

respectively).

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ontheforeignexchangemarketforSwedishkrona,ourinterviewshaveshownthat

thealgorithmsaremainlyappliedinspottrading,andtoalesserextentinforward7trade.

Aboveall,thisissaidtobebecausespottradingisthemoststandardisedformofforeign

exchangetrading,whileforwardtrademayinvolvespecificcharacteristicsandconditionsin

thetradedcontracts.Automatingforwardtradeisthusmoredifficultthanautomatingspot

trading.

Fromourinterviews,wedrawtheconclusionthatalgorithmsontheforeignexchange

marketforSwedishkronafulfilfourdifferentmainfunctions:executingorders;quoting

prices;managingrisks;andspeculatingandexploitingpricedifferenceswhenarbitrage

opportunitiesarise.

Order execution

Algorithmsareusedtoautomaticallyexecuteordersonthebasisofoneormore

predeterminedcriteria.Afewcommontypesofalgorithmsarethosethatspreadout

executionoverapredeterminedtimeperiod,executeanorderinbatchesofasmaller

amount,orexecuteanorderforacertainprice.Someallowarandomgeneratorto

determinetheamountconcernedoneachoccasionandwhenthetransactionistobe

executed.

Banksandtradingplatformsaredevelopingalgorithmsasapartoftheirrangeof

competitiveservicestoattractcustomersandultimatelygeneraterevenue.Forthe

customers,thealgorithmshaveentailedstandardisedandautomatedmethodsfor

minimisingmarketmanipulation,whentheycarryoutforeignexchangetransactionsand

enterordersanonymously.

Algorithmsalsomakeiteasierfortheusertoreportexactlyhowanorderhasbeen

executed,asallinformationisautomaticallystored.However,theassetmanagersandnon-

financialcompanies’treasurydepartmentsinterviewedsaythattheirusageofalgorithms

onlyamountstoatmost10percentofthetotalforeignexchangetransactionsinSwedish

krona.

Price quotation

certainalgorithmshavebeendevelopedtoautomaticallyquotepricesindifferentcurrency

pairs,sometimeswithveryhighfrequencies.withtheassistanceofsuchalgorithms,banks

cancontinuallyupdatetheirpricesfordifferentcurrencypairsonthetradingplatforms.

Thealgorithmsaresettoquotemarketpricesandactonthebasisoftheconditionsand

variablesforwhichtheyareprogrammed.consequently,undertherightconditions,they

makeitpossibleforthebankstorapidlyquotemarketprices,atthesametimeasmanual

involvementisminimisedandthenumberofworkinghoursperquotedpriceisreduced.

7 Aforwardisabindingagreementbetweentwopartiestobutorsellanunderlyingassetatacertainpriceatagivenpointintime.

– 8 –


Risk management

Somebanksusealgorithmstomanagethemarketrisksarisinginforeignexchange

transactions.oneexamplewouldbeifatransactiongeneratedbyacustomerledtoabank

buyinguSD/SeK,followingwhichanalgorithmsoldtheequivalentamountinuSD/SeKto

eliminatethemarketrisk.Suchalgorithmscanthusbesaidtoautomaticallymake

transactionstoachievethedesiredriskexposure.Furthermore,thesealgorithmsfreeup

resourcesforthebanks,asriskmanagementnolongerneedstobeconductedmanually.

Speculation and exploitation of arbitrage opportunities

Therearealsoalgorithmsthatcanbeusedtoautomaticallytakepositionstoyieldreturn.

Thedecisioncriteriathatthealgorithmsareprogrammedforaredefinedbythealgorithm’s

owners.Thesecriteriamay,forexample,bebasedoncorrelationsbetweenassettype

anddifferentcurrencypairsorotherhistoricalrelationships.Forexample,aspeculative

algorithmmaybeprogrammedtoselldollarswhenthepriceofgoldrises,asthehistorical

relationshiphasdemonstratedanegativecorrelationbetweentheseprices.Thepositions

generatedbyspeculativealgorithmsarethusassociatedwithmarketrisk.

Therearealsoalgorithmsthatdonottakeanymarketriskbuttakepositionswhen

arbitrageopportunitiesarisethroughinconsistenciesonpricing.Suchalgorithmscan,for

example,beprogrammedtorapidlyidentifyandactondifferencesinpricebetweena

derivativeanditsunderlyingassets,orbetweendifferentmarketplaces.Thisoftenmeans

thatinconsistenciesinpricingarerapidlyeliminated.

certainalgorithmsarehighfrequencytraders,whichistosaythattheytradeatavery

highfrequencyandbenefitfromtemporarypossibilitiestomakerisk-freeoralmostrisk-free

profitsthattheycanexploitduetotheirrapidity.Byexploitingavailableinformationearlier

andmorerapidlythanothermarketparticipants,theycanactfasteronnewinformation

andthusgenerateyield.However,noneofthemarketparticipantswehaveinterviewed

workswithsuchalgorithms.

4.ALGoRiTHMicFoReiGNexcHANGeTRADiNGLeADSToiNcReASeDeFFicieNcy

Thereareseveralconceivablereasonsfortheuseofalgorithmictradingonthefinancial

markets.oneoftheseisstructuralchangessuchaschangedregulationsformarketplaces,

whichHaldane(2011),amongothers,haveindicatedforthestockmarket.Forexample,the

conditionsforalgorithmictradingareinfluencedbywhethertradingisconductedononeor

severalmarketplaces,andbyaccesstodifferenttypesofmarketinformation.Thesefactors

can,inturn,dependontheregulationssurroundingtrading.

Anotherreasonforalgorithmictradingistechnologicaldevelopmentonthefinancial

markets.Algorithmictradingmeansthatthebankscanstreamlinetheirforeignexchange

tradingandprovidecompetitiveservicestotheircustomers.AccordingtotheBiS(2011),

highfrequencytradingontheforeignexchangemarket(forexample)isanincreasingly

commonformoftradingandpartofadevelopmentoftechnologythatisincreasingthe

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useofelectronictrading.Algorithmictradingisalsoreplacingoftenoldertechnologyby

fulfillingthesamefunctionsmoreefficiently.Forexample,Menkveld(2013)saysthat

highfrequencytradersonthestockmarkettoagreatextentresembletraditionalhuman

marketmakers.However,itislikelythattradingbytelephonewillcontinuetobeneededto

maketransactionswithlargeamounts.Theinterviewedmarketparticipantsdeemthatthe

personalrelationshipsbuiltupbyforeignexchangetradersbytelephonewillcontinuetobe

valuable,astheseareconsideredtoleadtofavourablebusinessconditionsandthusbetter

pricesinmajortransactions.

Technologicaldevelopmentisthusastrongcontributoryfactorinthegrowthofvarious

typesofalgorithmictrading.Technologicaldevelopmentoftenleadstoareductionin

thenumberofhoursneededtosupplyaservice,whichshouldmeanthatthemarketis

functioningmoreefficiently.Amongothercharacteristics,anefficientmarketissignifiedby

lowtransactioncostsandthepresenceofassetswithhighliquiditysothattheflowoftrade

canfunctionsmoothly(Fama,1970).

5.ALGoRiTHMicFoReiGNexcHANGeTRADiNGMAyeNTAiLRiSKS

However,thereareanumberofconceivableriskswithalgorithmictrading:operational

risks,riskswithregardtotheliquidityofthemarket,risksofincreasedvolatilityand

temporarycrashessuchasthe’flashcrash’in2010,riskstotheaccesstoinformationand

theconfidenceinthemarket,andrisksofbarriersofentryformarketmakers.Theserisks

existbothfortheindividualmarketparticipantandforthemarketasawhole.Theycan

alsovarydependingonhowliquidthecurrenciesare.Thisisbecausetheliquidityinthe

tradeofacurrencyinfluencesthechoiceofappropriatetradingstrategyandthedegreeto

whichtradingcanbeautomated.itisthereforeimportanttomakeadistinctionbetween

tradinginlessliquidcurrenciesandtradinginthemostliquidcurrencies.

AccordingtotheBiS(2010),theSwedishkronawasthecurrencywiththeninthhighest

turnoverinApril2010,with1.1percentoftheforeignexchangemarket’stotaldaily

turnoverofuSD4000billion.undernormalconditions,theliquidityoftheSwedishkrona

ishigh,meaningthatmarketparticipantscanmakeforeignexchangetransactionswithout

influencingexchangeratesagainstothercurrenciestoanygreatextent.However,during

certain,oftenturbulentperiods,theremayariseashortageofliquidityonthemarketfor

theSwedishkrona.Thismaymakeitdifficulttomaketransactionsatareasonableprice,as

thereissuddenlyverylittleinteresttotradeamongmarketparticipants.oneexampleof

thisisfollowingtheoutbreakofthefinancialcrisisin2008,whenthemarketparticipants

experiencedinsufficientliquidityonthemarket(SverigesRiksbank,2009).

Operational risks

Thealgorithmictradingmaycontributetoadecliningmanualhandlingoftransactions

andinteractionbetweenindividualstradingonthefinancialmarkets.Thismayhaveboth

benefitsanddrawbacks.oneadvantageisthattradingislessfrequentlyaffectedby

– 10 –


temporary,irrationalandoccasionallyimpulsivebehaviour.insteadofactingonthebasisof

emotions,thealgorithmsalwaysmakeassessmentsonthesamebasis,basedontheirpre-

programmedcriteria.

ontheotherhand,onedisadvantageofthedecreaseofmanualtradingmaybethat

algorithmsareunabletoquicklyassessscenariosforwhichtheyarenotprogrammed.

Forexample,ifamarketshouldsuddenlyloseliquidityorbesubjectedtoamajorfallin

prices,thereisariskthatthealgorithmwillnotchangeitsbehaviourbutwillcontinueto

tradeorquoteprices.Suchbehaviourmayleadtolossesforthemarketparticipantusing

thealgorithm.oneexampledatesfromAugust2012,whentheuSfinancecompany

KnightcapitallostuSD440millionafterthecompany’sincorrectlyprogrammedalgorithm

conductedloss-makingtransactionsin148differentstocks(FinancialTimes2,2012).

Market liquidity risks

Tomanageoperationalrisks,banksandothermarketparticipantsoftenusedifferent

typesofcircuitbreakersandothermechanismstodisablethealgorithmsinturbulent

situations.Thishelpsthemarketparticipantstoavoidlosses,butalsoleadstothesudden

disappearancefromthemarketplaceoftheliquidityotherwiseprovidedbythealgorithms’

trading.Kingetal.(2011)pointoutthatthereisuneasethathighfrequencytradingmarket

makersontheforeignexchangemarketmaychoosetostoptradingwhenturbulencearises

inmarketpricing.Thereareseveralstudiesofthisphenomenononthestockmarket.For

example,Johansson(2012)pointsouttheriskthatalgorithmictradersonthestockmarket

maystoptradingunderstressedmarketconditions.Suchbehaviourcanbothcreateand

worsenuneaseintrading,whichcanhaveanegativeeffectonmarketliquidity.

Severalstudiesshowthatalgorithmictradersusuallymakeapositivecontributionto

liquidityonthemarket.chaboudetal.(2011)indicatethatalgorithmictradingentails

increasedliquidityontheforeignexchangemarket,intermsofgreaterorderdepth.As

regardsthestockmarket,Hendershottetal.(2010)showthatalgorithmictradingon

thestockmarkethasgenerallycontributedpositivelytothemarket’sliquidity,butthat

anotherrelationshipcannotberuledoutunderstressedmarketconditions.Thebehaviour

ofalgorithmictraderscanalsobeexpectedtodiffer,dependingonwhichstrategythey

choosetoapply.HagströmerandNordén(2012)dividehighfrequencytradersintomarket

makersandopportunistictraders.Theyshowthatthemarketmakersarethedominant

highfrequencytradersontheSwedishstockmarketandthattheycontributepositivelyto

liquidityonthemarket.Gomberetal.(2011)alsopointoutthatthetraders’strategiesform

areasonablestartingpointfortheassessmentofhighfrequencytrading.

Risks of increased volatility and temporary crashes

Algorithmictradingthattakesplaceforspeculativepurposesortoexploitarbitrage

opportunitiescanaffectthepricingofcurrenciesandotherassetclasses.Bicchettiand

Maystre(2012)showthatinconsistenciesinpricingbetweendifferentassetclassesand

– 11 –


currencies,andbetweenderivativesandtheirunderlyingassets,areexpectedtobecome

fewer.Suchadevelopmentcanbeseenaspositive,asitwillleadtoamorearbitrage-free

market.chaboudetal.(2011)alsoshowthatalgorithmictradinghasledtofewerarbitrage

opportunities,asthemarketreactsmorequicklytonewinformation.Thisdevelopment

couldalsobeimaginedtoleadtoincreasedco-variancebetweendifferentfinancial

instrumentsandbetweendifferentassetmarkets,asnewinformationismorerapidly

reflectedinprices.

Authoritiesandresearchershaveaskedwhetheralgorithmictradingmayleadto

increasedvolatilityinassetprices,whichcouldimpairthefunctioningofthefinancial

markets.Severalstudieshavebeenmadeofthisrelationshiponthestockmarket.Boehmer

etal.(2012)indicateapositiverelationbetweenalgorithmictradingandvolatilityonthe

stockmarket,thatisthatalgorithmictradingcontributestoincreasedvolatility.Atthesame

time,therearestudiesthatindicatetheopposite,forexampleHagströmerandNordén

(2012).Broogaardetal.(2012)cannotdrawanyconclusionsindicatinganyclearrelation

betweenhighfrequencytradingandvolatility.Asregardstheforeignexchangemarket,

chaboudetal.(2011)shownoclearsignsthatalgorithmictradinginfluencesvolatility.in

general,thereisthusalackofsupportforaclearrelationbetweenalgorithmictradingand

volatility.

However,theGovernmentofficeforScience(2012)demonstratesthatalgorithmson

thestockmarketcanactinakindoftechnologicalherdbehaviour,socalledfeedback

loops,whichcancreaterapidpricefluctuations.ontheseoccasions,algorithmsactby

sellingorbuyingsimultaneously,whichaffectsthepriceoftheassetinquestioneither

upwardsordownwards.Asregardstheforeignexchangemarket,chaboudetal.(2011)

showthatthealgorithmictraders’strategiesshowmoreofacorrelationthandothose

ofthehumantraders.Asdifferentfinancialinstrumentsandmarketsco-varymore,a

temporaryandexaggeratedmarketfluctuationononeassetmarketcanspreadtothe

foreignexchangemarket,whichcancreateuncertaintyonseveralfinancialmarkets.Sucha

scenariowouldbeparticularlyseriousforacurrencyliketheSwedishkrona,whichdoesnot

belongtothemostliquidcurrencies,asitmayleadtoasuddenreductionofliquidityonthe

market.

However,accordingtotheBiS(2011),theriskoftemporarycrashesissmalleron

theforeignexchangemarketthanitisonthestockmarket.Thisisbecausetheforeign

exchangemarketdiffersfromthestockmarketinseveralrespects.onefundamental

difference,accordingtothereport,isthatacurrencyispricedinrelationtoanother

currency,whileastockpriceisanabsoluteprice.whenthepriceofacurrencyfalls,one

partyloses,whiletheotherpartygains.Thismeansaredistributionofwealthratherthan

areduction,whichistheeffectwhenstockpricesfall.Afurtherdifferenceisthatthereis

ratherstabledemandforforeignexchangerelatedtocross-bordertradeandfinancialflows.

Thereisnoequivalentflowonthestockmarket.

– 12 –


Risk related to the access to information and the confidence in the market

Anunevendistributionofinformationmayleadslowerinvestorstomakelessadvantageous

investmentdecisionsthanhighfrequencytraders,astheydonotreceiveinformationas

rapidly.Biaisetal.(2011),Jarrowetal.(2011)andMcinishandupson(2012)discussthis

andnotethathighfrequencytradershavevariousmeansofprofitingfromandactingon

informationmorerapidlythanothermarketparticipants.Finansinspektionen(2012)and

Johansson(2012)discusstheriskofimproperbehaviourandreachtheconclusionthathigh

frequencytradinggivesrisetonewbehaviouramongmarketparticipantsthatmayentail

ariskofmarketabuse.inthattradingtakesplaceatahigherspeed,thusthepossibilityof

improperlyinfluencingthemarketpricetoatrader’sownadvantage.

However,therearealsostudiesthatshowthathighfrequencytradersquotethemost

favourablepricesonthemarketandthuscontributetowardsefficientpriceformation.

ThesestudiesincludeHasbrouckandSaar(2011).Asregardstheforeignexchangemarket,

chaboudetal.(2011)simultaneouslyshowthatthepeoplewhoaretradingstillhavegood

accesstoinformationandthattheirtradinginfluencespriceformationmorethanthatofthe

algorithmictraders.

Risks of barriers of entry for market makers

Developingalgorithmsrequiresmoreorlesscomprehensiveinvestmentsintechnology.

Thosebanksinvestinginelectronicsystemsandalgorithmsdosopartlytostreamlinetheir

operationstogaineconomiesofscaleoverotherbanks.AccordingtoKingetal.(2011),this

isanexampleofareasonforthebankstochoosetodeveloptheirowntradingplatformsfor

customertradingtoagreaterextent.Thismakesitpossibleforthebankstointernallymatch

cashflowsindifferentcurrencies.Atthesametime,asthismayhaveadvantagesforthe

individualbanks,Kingetal.(2011)observethatanincreasedfragmentationofthemarket

may,overthelongterm,occasionallycreateliquidityshortagesontheinterbankmarket.

Thereisalsoariskthattheneedforcomprehensiveinvestmentswillcreatebarriersof

entryontheforeignexchangemarket.Thisisbecausesmallbankscanlackboth

competenceandresourcestoinvestinthetechnologyneededtocompetefortrade.King

etal.(2011)statethatsuchbarriersofentryhaveledfewerbankstochoosenottobeactive

inthelargest,mostliquidcurrencypairs.Atthesametime,Kingetal.(2011)saythatthe

smallerbanksarestilltradinginthesmallerlocalcurrencies,andthattheyarethereby

becomingexpertsandearningmoneyontradewiththesecurrencies.

6.ScoPeFoRSeLF-ReGuLATioNiNTHeFuTuRe

ingeneral,theforeignexchangemarketdiffersfromotherfinancialmarkets,asforeign

exchangetradingandtheclearingandsettlementofforeignexchangetransactionsare

notregulatedbyauthorities.Atpresent,thereisnoSwedishlegislationtoregulatetrading

ontheforeignexchangemarket.However,itisinthemarket’sowninteresttocounteract

tradingthatmaydamagethefunctioningofthemarket.itisthereforeself-regulatingin

– 13 –


thatthemarketitselfhasformulatedapracticeforhowtradefunctions.Neitheristhereany

globallegislationforthetradingplatformsexistingforforeignexchangetrading,whichisa

differencetohowthestockmarketfunctions(BiS,2011).

Sincethefinancialcrisis,workhasstartedontheformulationofseveralnewregulatory

frameworks.However,undertheircurrentformulations,noneoftheseregulatory

frameworksspecificallyaffecttheforeignexchangemarket.intheeu,MiFiDii/MiFiR8

willentailexpandedregulationsfortheequityandfixed-incomemarkets(bothspotand

derivativemarkets),amongotherareasregardingincreasedtransparencyandrequirements

coveringwhichinstrumentsmaybetradedonaregulatedmarketplace.Thereareatpresent

noequivalentrulesfortheforeignexchangemarket.MiFiDiiwillprobablyalsoincluderules

placingrequirementsonsecuritiescompaniesusingalgorithmictrading(articles17and51

oftheeuropeancommission,2011).inasimilarway,theso-calledDodd-FrankActinthe

unitedStateswillprobablyincludenewrulesonalgorithmictrading.itisnotcompletelyclear

whetherandhowsecuritiescompaniesusingalgorithmictradingincurrencywillbeaffected

bytheseregulations.Thelegislationisprimarilyintendedtoaddressanynegativeeffectsof

highfrequencytradingonthestockmarket.

Recently,certaintradingplatformshavetriedtocounteractelementsofalgorithmic

trading,asithasbeenseenasdisruptivetothefunctioningoftheforeignexchangemarket.

oneexampleofsuchaplatformiseBS.Themeasuresadoptedincludeanincreasedtick

size9,aswellasareductionofthenumberofbidsatradermayenterwithoutactually

trading.Tradingbehaviourisdeemedtohavebecomehealthierduetothesemeasures,

withouttradingvolumeshavingbeenaffectednegatively(FinancialTimes1,2012).There

willcontinuetobescopeforthiskindofself-regulationtocounteractelementsofdisruptive

tradingontheforeignexchangemarket.

8 MiFiDstandsfortheMarketsinFinancialinstrumentsDirective.MiFiRstandsforMarketsinFinancialinstrumentsRegulation.Theseregulationswillprobablybeimplementedin2015.

9 Ticksizeisthesmallestpossiblepricechange.

– 14 –


References

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ioSco(2011).RegulatoryissuesRaisedbytheimpactofTechnologicalchangesonMarketintegrityandefficiency.TechnicalcommitteeoftheinternationalorganizationofSecuritiescommissions.consultationreport.July2011.

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Johansson,N.(2012).Högfrekventochalgoritmiskhandel–enöversikt(“Highfrequencyandalgorithmictrading–anoverview”).ReporttoFinansinspektionen.21February2012.

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King,M.R.,osler,c.,&Dagfinn,R.(2011).Foreignexchangemarketstructure,playersandevolution.NorgesBankResearchDepartment.workingPaper.No.2011/10.14August2011.

Kirilenko,A.,Kyle,A.S.,Samadi,M.,&Tuzun,T.(2011).TheFlashcrash:TheimpactofHighFrequencyTradingonanelectronicMarket.workingPaper.18January2011.

Mcinish,T.,&upson,J.(2012).StrategicLiquiditySupplyinaMarketwithFastandSlowTraders.workingPaper.1March2012.

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