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Neural Network Definition - Investopedia

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A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the ... AlgorithmicTrading AutomatedTrading WhatIsaNeuralNetwork? Aneuralnetworkisaseriesofalgorithmsthatendeavorstorecognizeunderlyingrelationshipsinasetofdatathroughaprocessthatmimicsthewaythehumanbrainoperates.Inthissense,neuralnetworksrefertosystemsofneurons,eitherorganicorartificialinnature. Neuralnetworkscanadapttochanginginput;sothenetworkgeneratesthebestpossibleresultwithoutneedingtoredesigntheoutputcriteria.Theconceptofneuralnetworks,whichhasitsrootsinartificialintelligence,isswiftlygainingpopularityinthedevelopmentoftradingsystems. ImagebySabrinaJiang©Investopedia 2020 KeyTakeaways Neuralnetworksareaseriesofalgorithmsthatmimictheoperationsofananimalbraintorecognizerelationshipsbetweenvastamountsofdata.Assuch,theytendtoresembletheconnectionsofneuronsandsynapsesfoundinthebrain.Theyareusedinavarietyofapplicationsinfinancialservices,fromforecastingandmarketingresearchtofrauddetectionandriskassessment.Neuralnetworkswithseveralprocesslayersareknownas"deep"networksandareusedfordeeplearningalgorithmsThesuccessofneuralnetworksforstockmarketpricepredictionvaries. BasicsofNeuralNetworks Neuralnetworks,intheworldoffinance, assistinthedevelopmentofsuchprocessesastime-seriesforecasting,algorithmictrading,securitiesclassification,creditriskmodeling,andconstructingproprietaryindicatorsandpricederivatives. Aneuralnetworkworkssimilarlytothehumanbrain’sneuralnetwork.A“neuron”inaneuralnetworkisamathematicalfunctionthatcollectsandclassifiesinformationaccordingtoaspecificarchitecture.Thenetworkbearsastrongresemblancetostatisticalmethodssuchascurvefittingandregressionanalysis. Aneuralnetworkcontainslayersofinterconnectednodes.Eachnodeisaknownasperceptronandissimilartoamultiplelinearregression.Theperceptronfeedsthesignalproducedbyamultiplelinearregressionintoanactivationfunctionthatmaybenonlinear. Multi-LayeredPerceptron Inamulti-layeredperceptron(MLP),perceptronsarearrangedininterconnectedlayers.Theinputlayercollectsinputpatterns.Theoutputlayerhasclassificationsoroutputsignalstowhichinputpatternsmaymap.Forinstance,thepatternsmaycomprisealistofquantitiesfortechnicalindicatorsaboutasecurity;potentialoutputscouldbe“buy,”“hold”or“sell.” Hiddenlayersfine-tunetheinputweightingsuntiltheneuralnetwork’smarginoferrorisminimal.Itishypothesizedthathiddenlayersextrapolatesalientfeaturesintheinputdatathathavepredictivepowerregardingtheoutputs.Thisdescribesfeatureextraction,whichaccomplishesautilitysimilartostatisticaltechniquessuchasprincipalcomponentanalysis. ApplicationofNeuralNetworks Neuralnetworksarebroadlyused,withapplicationsforfinancialoperations,enterpriseplanning,trading,businessanalytics,andproductmaintenance.Neuralnetworkshavealsogainedwidespreadadoptioninbusinessapplicationssuchasforecastingandmarketingresearchsolutions,frauddetection,andriskassessment. Aneuralnetworkevaluatespricedataandunearthsopportunitiesformakingtradedecisionsbasedonthedataanalysis.Thenetworkscandistinguishsubtlenonlinearinterdependenciesandpatternsothermethodsoftechnicalanalysiscannot.Accordingtoresearch,theaccuracyofneuralnetworksinmakingpricepredictionsforstocksdiffers.Somemodelspredictthecorrectstockprices50to60percentofthetime,whileothersareaccuratein70percentofallinstances.Somehavepositedthata10percentimprovementinefficiencyisallaninvestorcanaskforfromaneuralnetwork. Therewillalwaysbedatasetsandtaskclassesthatabetteranalyzedbyusingpreviouslydevelopedalgorithms.Itisnotsomuchthealgorithmthatmatters;itisthewell-preparedinputdataonthetargetedindicatorthatultimatelydeterminesthelevelofsuccessofaneuralnetwork. WhatAretheComponentsofaNeuralNetwork? Therearethreemaincomponents:aninputlater,aprocessinglayer,andanoutputlayer.Theinputsmaybeweightedbasedonvariouscriteria.Withintheprocessinglayer,whichishiddenfromview,therearenodesandconnectionsbetweenthesenodes,meanttobeanalogoustotheneuronsandsynapsesinananimalbrain. WhatIsaConvolutionalNeuralNetwork? Aconvolutionalneuralnetworkisoneadaptedforanalyzingandidentifyingvisualdatasuchasdigitalimagesorphotographs. WhatIsaRecurrentNeuralNetwork? Arecurrentneuralnetworkisoneadaptedforanalyzingtimeseriesdata,eventhistory,ortemporalordering. WhatIsaDeepNeuralNetwork? Alsoknownasadeeplearningnetwork,adeepneuralnetwork,atitsmostbasic,isonethatinvolvestwoormoreprocessinglayers. ArticleSources Investopediarequireswriterstouseprimarysourcestosupporttheirwork.Theseincludewhitepapers,governmentdata,originalreporting,andinterviewswithindustryexperts.Wealsoreferenceoriginalresearchfromotherreputablepublisherswhereappropriate.Youcanlearnmoreaboutthestandardswefollowinproducingaccurate,unbiasedcontentinour editorialpolicy. SpringerLink."AnInnovativeNeuralNetworkApproachforStockMarketPrediction."AccessedSept.23,2020. CompareAccounts AdvertiserDisclosure × TheoffersthatappearinthistablearefrompartnershipsfromwhichInvestopediareceivescompensation.Thiscompensationmayimpacthowandwherelistingsappear.Investopediadoesnotincludealloffersavailableinthemarketplace. Provider Name Description RelatedTerms ReadingIntoPredictiveModeling Predictivemodelingistheprocessofusingknownresultstocreate,process,andvalidateamodelthatcanbeusedtoforecastfutureoutcomes. more PredictiveAnalyticsDefinition Predictiveanalyticsistheuseofstatisticsandmodelingtechniquestodeterminefutureperformancebasedoncurrentandhistoricaldata. more TechnicalSkillsDefinition Technicalskillsaretheabilitiesandknowledgeneededtocompletepracticaltasks.Whichtechnicalskillsshouldyouputonaresume?Weanswerthathere. more WhatIsFuzzyLogic? Fuzzylogicisamathematicallogicthatsolvesproblemswithanopen,imprecisedataspectrum.Readhowtoobtainaccurateconclusionswithfuzzylogic. more HowtheResidualSumofSquares(RSS)Works Theresidualsumofsquares(RSS)isastatisticaltechniqueusedtomeasurethevarianceinadatasetthatisnotexplainedbytheregressionmodel. more WhatIsNonlinearity? Optionshaveahighdegreeofnonlinearity,whichmaymakethemseemunpredictable.Learnaboutnonlinearityandhowtomanageyouroptionstradingrisk. more PartnerLinks RelatedArticles Sectors&Industries NeuralNetworks:ForecastingProfits High-FrequencyTrading(HFT) NewAlternativestoHigh-FrequencyTrading Degrees&Certifications DataAnalyst:CareerPathandQualifications Macroeconomics HowDoCompaniesForecastOilPrices? TradingStrategies HowStatisticalArbitrageCanLeadtoBigProfits AutomatedTrading CodingYourOwnAlgo-TradingRobot

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