dc.contributor.author | Maknickienė, Nijolė | |
dc.date.accessioned | 2023-09-18T20:03:27Z | |
dc.date.available | 2023-09-18T20:03:27Z | |
dc.date.issued | 2014 | |
dc.identifier.other | (BIS)VGT02-000028124 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/146315 | |
dc.description.abstract | Investing in financial market require the reliable predicting of expecting returns, assessment of risk and reliability. Principle of portfolio orthogonality was using to reduce the risk of the investment. An artificial intelligence system may reveal new opportunities for using this principle. Prediction of recurrent neural networks ensemble is stochastically informative distribution, which is helpful for portfolio selection. Shape and parameters of distribution influence decision making in currency market. Assessment of portfolio riskiness, finding most orthogonal elements of portfolio, influence better results for trading in real market. | eng |
dc.format | PDF | |
dc.format.extent | p. 1158-1165 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.ispartofseries | Procedia - social and behavioral sciences vol. 110 1877-0428 | |
dc.relation.isreferencedby | Conference Proceedings Citation Index - Science (Web of Science) | |
dc.relation.isreferencedby | ScienceDirect | |
dc.source.uri | https://doi.org/10.1016/j.sbspro.2013.12.962 | |
dc.source.uri | http://www.sciencedirect.com/science/article/pii/S1877042813056024 | |
dc.subject | VE01 - Aukštos pridėtinės vertės ekonomika / High value-added economy | |
dc.title | Selection of orthogonal investment portfolio using evolino RNN trading model | |
dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
dcterms.references | 38 | |
dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Verslo vadybos fakultetas / Faculty of Business Management | |
dc.contributor.department | Finansų inžinerijos katedra / Department of Financial Engineering | |
dc.subject.researchfield | S 004 - Ekonomika / Economics | |
dc.subject.ltspecializations | L103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society | |
dc.subject.en | artificial intelligence | |
dc.subject.en | forecasting | |
dc.subject.en | ensembles | |
dc.subject.en | prediction | |
dc.subject.en | portfolio management | |
dcterms.sourcetitle | The 2-dn International scientific conference „Contemporary issues in business, management and education 2013" | |
dc.publisher.name | Elsevier | |
dc.publisher.city | Amsterdam | |
dc.identifier.doi | 000466711800120 | |
dc.identifier.doi | 10.1016/j.sbspro.2013.12.962 | |
dc.identifier.elaba | 4067205 | |