dc.rights.license | Kūrybinių bendrijų licencija / Creative Commons licence | en_US |
dc.contributor.author | Maknickienė, Nijolė | |
dc.contributor.author | Maknickas, Algirdas | |
dc.date.accessioned | 2024-04-25T13:55:14Z | |
dc.date.available | 2024-04-25T13:55:14Z | |
dc.date.issued | 2016 | |
dc.identifier.issn | 2029-4441 | en_US |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/154074 | |
dc.description.abstract | Forecasting of chaotic changes of exchange rates usually is based on historical data and depends on the choice of time intervals. This study seeks to develop new forecasting method based on data of different time zones. This paper demonstrates how the using of London and New York divisions of the trading day allows getting additional information from predicting exchange rates. This was modelled with the help of ensemble of EVOLINO for obtaining of predictions of the distribution of expected values. The obtained results show that double forecasts evaluation reveals a possible trend in the exchange market and enriches the choice of real-time trading strategies. | en_US |
dc.format.extent | 8 p. | en_US |
dc.format.medium | Tekstas / Text | en_US |
dc.language.iso | en | en_US |
dc.relation.uri | https://etalpykla.vilniustech.lt/handle/123456789/154000 | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source.uri | https://bm.vilniustech.lt/index.php/verslas/2016/paper/view/30 | en_US |
dc.subject | artificial intelligence | en_US |
dc.subject | evolino | en_US |
dc.subject | ensemble | en_US |
dc.subject | forecasting composition | en_US |
dc.subject | investment | en_US |
dc.subject | speculation | en_US |
dc.subject | support system | en_US |
dc.title | Impact of time zones on forecasting of exchange market based on distribution of expected values | en_US |
dc.type | Konferencijos publikacija / Conference paper | en_US |
dcterms.accessRights | Laisvai prieinamas / Openly available | en_US |
dcterms.accrualMethod | Rankinis pateikimas / Manual submission | en_US |
dcterms.alternative | Finance engineering | en_US |
dcterms.issued | 2016-05-13 | |
dcterms.license | CC BY | en_US |
dcterms.references | 40 | en_US |
dc.description.version | Taip / Yes | en_US |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | en_US |
dc.contributor.institution | Vilnius Gediminas technical university | en_US |
dc.contributor.faculty | Verslo vadybos fakultetas / Faculty of Business Management | en_US |
dc.contributor.faculty | Fundamentinių mokslų fakultetas / Faculty of Fundamental Science | |
dc.contributor.department | Informacinių technologijų katedra / Department of Information Technologies | en_US |
dc.contributor.department | Finansų inžinerijos katedra / Department of Finance Engineering | |
dcterms.sourcetitle | 9th International Scientific Conference “Business and Management 2016” | en_US |
dc.identifier.eisbn | 9786094579219 | en_US |
dc.identifier.eissn | 2029-929X | en_US |
dc.publisher.name | Vilnius Gediminas Technical University | en_US |
dc.publisher.name | Vilniaus Gedimino technikos universitetas | en_US |
dc.publisher.country | Lithuania | en_US |
dc.publisher.country | Lietuva | en_US |
dc.publisher.city | Vilnius | en_US |
dc.identifier.doi | https://doi.org/10.3846/bm.2016.29 | en_US |