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dc.contributor.authorStankevičienė, Jelena
dc.contributor.authorMaknickienė, Nijolė
dc.contributor.authorMaknickas, Algirdas
dc.date.accessioned2023-09-18T16:53:28Z
dc.date.available2023-09-18T16:53:28Z
dc.date.issued2017
dc.identifier.issn1392-2785
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/117797
dc.description.abstractStrategy of investment is important tool enabling better investor’s decisions in uncertain finance market. Rules of portfolio selection help investors balance accepting some risk for the expectation of higher returns. The aim of the research is to propose strategy of constructing investment portfolios based on the composition of distributions obtained by using high– low data. The ensemble of 176 Evolino recurrent neural networks (RNN) trained in parallel investigated as an artificial intelligence solution, which applied in forecasting of financial markets. Predictions made by this tool twice a day with different historical data give two distributions of expected values, which reflect future dynamic exchange rates. Constructing the portfolio, according to the shape, parameters of distribution and the current value of the exchange rate allows the optimization of trading in daily exchange-rate fluctuations. Comparison of a high-low portfolio with a close-to-close portfolio shows the efficiency of the new forecasting tool and new proposed trading strategy.eng
dc.formatPDF
dc.format.extentp. 162-169
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyCEEOL – Central and Eastern European Online Library
dc.relation.isreferencedbyBusiness Source Complete
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.source.urihttp://dx.doi.org/10.5755/j01.ee.28.2.15852
dc.subjectVE - Technologijų vadyba ir ekonomika / Technology management and economics
dc.titleHigh-low strategy of portfolio composition using Evolino RNN ensembles
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references45
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Management
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.contributor.departmentFinansų inžinerijos katedra / Department of Financial Engineering
dc.subject.researchfieldS 004 - Ekonomika / Economics
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.enFinance markets
dc.subject.enEvolino, High-low strategy
dc.subject.enInvestment portfolio
dc.subject.enPrediction.
dcterms.sourcetitleInžinerinė ekonomika = Engineering economics
dc.description.issueno. 2
dc.description.volumeVol. 28
dc.publisher.nameKTU
dc.publisher.cityKaunas
dc.identifier.doi000402649600005
dc.identifier.doi10.5755/j01.ee.28.2.15852
dc.identifier.elaba22270180


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