Rodyti trumpą aprašą

dc.contributor.authorStankevičienė, Jelena
dc.contributor.authorMaknickienė, Nijolė
dc.contributor.authorMaknickas, Algirdas
dc.date.accessioned2024-06-20T08:40:25Z
dc.date.available2024-06-20T08:40:25Z
dc.date.issued2014
dc.identifier.isbn9786094576508en_US
dc.identifier.issn2029-4441en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/154507
dc.description.abstractThe model of Evolino recurrent neural networks (RNN) based on ensemble for prediction of daily extremes of financial market is investigated. The prediction distributions of each high and lows of daily values of exchange rates were obtained. Obtained distributions show an accuracy of predictions, reflects true features of direct time interval unpredictability of chaotic process. Changing of time series data from close to extremes allows to create new strategy of investment built on distributions basic parameters: standard deviation, skewness, kurtosis. Extension of close distribution to the pair of high-low distribution is opening extra capabilities of optimal portfolio creation and risk management for investors.en_US
dc.format.extent8 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/154365en_US
dc.source.urihttp://old.konferencijos.vgtu.lt/bm.vgtu.lt/public_html/index.php/bm/bm_2014/paper/view/300en_US
dc.subjectartificial intelligenceen_US
dc.subjectensembleen_US
dc.subjectEvolino RNNen_US
dc.subjectexchange marketen_US
dc.subjectforecastingen_US
dc.subjectpredictionen_US
dc.subjectdistributionen_US
dc.titleInvestigation of exchange market prediction model based on high-low daily dataen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accessRightsLaisvai prieinamas / Openly availableen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.alternativeFinance engineeringen_US
dcterms.issued2014-05-16
dcterms.references34en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionVilniaus Gedimino technikos universitetasen_US
dc.contributor.institutionVilnius Gediminas Technical Universityen_US
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Managementen_US
dcterms.sourcetitle8th International Scientific Conference “Business and Management 2014”en_US
dc.identifier.eisbn9786094576492en_US
dc.identifier.eissn2029-929Xen_US
dc.publisher.nameVilnius Gediminas Technical Universityen_US
dc.publisher.nameVilniaus Gedimino technikos universitetasen_US
dc.publisher.countryLithuaniaen_US
dc.publisher.countryLietuvaen_US
dc.publisher.cityVilniusen_US
dc.identifier.doihttp://dx.doi.org/10.3846/bm.2014.040en_US


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