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1、JOURNALOFSTELLARMS&E444REPORTS1AdaptiveStrategiesforHighFrequencyTradingErikAndersonandPaulMerollaandAlexisPribulaTockpricesonelectronicexchangesaredeterminedateachtickbyamatchingalgorithmwhichmatchesbuyerswithSsellers,whocanbethoughtofasindependentagentsnegotiatingoveranacceptabl
2、epurchaseorsellprice.Exchangesmaintainan“orderbook”whichisalistofthebidandaskorderssubmittedbytheseindependentagents.Ateachtick,therewillbeadistributionofbidandaskordersontheorderbook.Notonlywilltherebeavariationinthebidandaskprices,buttherewillbeavariationinthenumbersofsharesavai
3、lableateachprice.Forinstanceat11:00:00onFebruary12,2008,theorderbookontheChicagoMercantileExchangecarriedthequotesfortheEScontractasshownbelow:BidAsk#BidShares#OfferShares13621362.2581791361.751362.56109551361.501362.7593413401361.251363815178613611363.2514921335Thegoalofthisproje
4、ctwastoexplorewhethertheorderbookisanimportantsourceofinformationforpredictingshort-termfluctuationsofstockreturns.Intuitively,onewouldexpectthatwhentherateandsizeofbuyordersexceedsthatofsellorders,thestockpricewouldhaveapropensitytodriftup.Whetherthishappensornotultimatelydependso
5、nhowtheagentsreactandupdatetheirtradingstrategies.Ourhopeisthatbyconsideringtheorderbook,wecanbetterpredictagentbehaviorsandtheireffectonmarketdynamics,asopposedtoapredictionmethodthatdidnotconsiderthebook.Therewerethreephasestoourproject.Firstweobtainedanadequatehistoricaldatasou
6、rce(SectionI),fromwhichweextractedmetricsbasedontheorderbook(SectionII).Next,wedevelopedanadaptivefilteringalgorithmthatwasdesignedforshort-termprediction(SectionIII).Toevaluateourpredictionmethod,wecreatedasimulatedtradingenvironmentandbacktestedasimpletradingstrategyformarketmaki
7、ng(SectionsIV,V,&VI).Wediscoveredthatourpredictiontechniqueworkswellforthemostpart,however,coordinatedmarketmovements(sometimescalledmarketshocks)oftenresultedinlargelosses.Thefinalphaseofprojectwastoemployamoresophisticatedmachinelearningtechnique,supportvectormachines(SVMs),tofor
8、ecastupcomingshocksandjudiciously
