DC ElementWertSprache
dc.contributor.authorVoigt, Frederic-
dc.contributor.authorAlcarez Calero, Jose-
dc.contributor.authorDahal, Keshav-
dc.contributor.authorWang, Qi-
dc.contributor.authorvon Luck, Kai-
dc.contributor.authorStelldinger, Peer-
dc.date.accessioned2025-08-15T06:02:29Z-
dc.date.available2025-08-15T06:02:29Z-
dc.date.issued2024-12-10-
dc.identifier.isbn979-8-3503-5483-6en_US
dc.identifier.isbn979-8-3503-5484-3en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12738/18037-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectquantitative analysisen_US
dc.subjectstock embeddingsen_US
dc.subjectstock movement predictionen_US
dc.subjectstock price predictionen_US
dc.subject.ddc004: Informatiken_US
dc.titleQuantitative Market Situation Embeddings: Utilizing Doc2Vec Strategies for Stock Dataen
dc.typeinProceedingsen_US
dc.relation.conferenceIEEE Symposium on Computational Intelligence for Financial Engineering and Economics 2024en_US
dc.identifier.scopus2-s2.0-85214975328en
dc.description.versionPeerRevieweden_US
local.contributorCorporate.editorInstitute of Electrical and Electronics Engineers-
tuhh.oai.showtrueen_US
tuhh.publication.instituteDepartment Informatiken_US
tuhh.publication.instituteFakultät Technik und Informatiken_US
tuhh.publisher.doi10.1109/CIFER62890.2024.10772772-
tuhh.relation.ispartofseries2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr) : 22-23 Oct. 2024en_US
tuhh.type.opusInProceedings (Aufsatz / Paper einer Konferenz etc.)-
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dc.type.casraiConference Paper-
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dc.type.statusinfo:eu-repo/semantics/publishedVersionen_US
dcterms.DCMITypeText-
dc.contributor.departmentcityAyren
dc.contributor.departmentcityAyren
dc.contributor.departmentcityAyren
dc.contributor.departmentcityAyren
dc.contributor.departmentcityHamburgen
dc.contributor.departmentcityHamburgen
dc.contributor.departmentcountryUnited Kingdomen
dc.contributor.departmentcountryUnited Kingdomen
dc.contributor.departmentcountryUnited Kingdomen
dc.contributor.departmentcountryUnited Kingdomen
dc.contributor.departmentcountryGermanyen
dc.contributor.departmentcountryGermanyen
dc.contributor.departmenturlhttps://api.elsevier.com/content/affiliation/affiliation_id/60097343en
dc.contributor.departmenturlhttps://api.elsevier.com/content/affiliation/affiliation_id/60097343en
dc.contributor.departmenturlhttps://api.elsevier.com/content/affiliation/affiliation_id/60097343en
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item.languageiso639-1en-
item.grantfulltextnone-
item.creatorGNDVoigt, Frederic-
item.creatorGNDAlcarez Calero, Jose-
item.creatorGNDDahal, Keshav-
item.creatorGNDWang, Qi-
item.creatorGNDvon Luck, Kai-
item.creatorGNDStelldinger, Peer-
item.openairetypeinProceedings-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.creatorOrcidVoigt, Frederic-
item.creatorOrcidAlcarez Calero, Jose-
item.creatorOrcidDahal, Keshav-
item.creatorOrcidWang, Qi-
item.creatorOrcidvon Luck, Kai-
item.creatorOrcidStelldinger, Peer-
item.tuhhseriesid2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr) : 22-23 Oct. 2024-
item.seriesref2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr) : 22-23 Oct. 2024-
crisitem.author.deptDepartment Informatik-
crisitem.author.deptDepartment Informatik-
crisitem.author.orcid0000-0001-8079-2797-
crisitem.author.parentorgFakultät Technik und Informatik-
crisitem.author.parentorgFakultät Technik und Informatik-
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