Quantitative Market Situation Embeddings: Utilizing Doc2Vec Strategies for Stock Data

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Beteiligte Personen:
  • #NODATA#
  • #NODATA#
  • #NODATA#
  • #NODATA#
  • #NODATA#
  • #NODATA#
  • Ayr
  • Ayr
  • Ayr
  • Ayr
  • Hamburg
  • Hamburg
  • United Kingdom
  • United Kingdom
  • United Kingdom
  • United Kingdom
  • Germany
  • Germany
  • https://api.elsevier.com/content/affiliation/affiliation_id/60097343
  • https://api.elsevier.com/content/affiliation/affiliation_id/60097343
  • https://api.elsevier.com/content/affiliation/affiliation_id/60097343
  • https://api.elsevier.com/content/affiliation/affiliation_id/60097343
  • https://api.elsevier.com/content/affiliation/affiliation_id/60032697
  • https://api.elsevier.com/content/affiliation/affiliation_id/60032697
Verlag/Körperschaft:
IEEE
Erscheinungsjahr:
2024
Medientyp:
Text
Schlagworte:
  • quantitative analysis
  • stock embeddings
  • stock movement prediction
  • stock price prediction
  • 004: Informatik
  • ddc:004
Beschreibung:
  • PeerReviewed
Quellsystem:
ReposIt
Interne Metadaten
Quelldatensatz
oai:reposit.haw-hamburg.de:20.500.12738/18037