How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations (2025)
- Authors:
- USP affiliated authors: MARCACINI, RICARDO MARCONDES - ICMC ; REZENDE, SOLANGE OLIVEIRA - ICMC ; GÔLO, MARCOS PAULO SILVA - ICMC
- Unidade: ICMC
- DOI: 10.1007/s00521-024-10418-5
- Subjects: APRENDIZADO COMPUTACIONAL; REDES NEURAIS; PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS); MERCADO FINANCEIRO
- Keywords: Time series; Text embeddings; Graph
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Neural Computing and Applications
- ISSN: 0941-0643
- Volume/Número/Paginação/Ano: v. 37, n. 3, p. 1307-1319, Jan. 2025
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
REIS FILHO, Ivan José dos et al. How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations. Neural Computing and Applications, v. 37, n. Ja 2025, p. 1307-1319, 2025Tradução . . Disponível em: https://doi.org/10.1007/s00521-024-10418-5. Acesso em: 09 fev. 2026. -
APA
Reis Filho, I. J. dos, Gôlo, M. P. S., Marcacini, R. M., & Rezende, S. O. (2025). How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations. Neural Computing and Applications, 37( Ja 2025), 1307-1319. doi:10.1007/s00521-024-10418-5 -
NLM
Reis Filho IJ dos, Gôlo MPS, Marcacini RM, Rezende SO. How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations [Internet]. Neural Computing and Applications. 2025 ; 37( Ja 2025): 1307-1319.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1007/s00521-024-10418-5 -
Vancouver
Reis Filho IJ dos, Gôlo MPS, Marcacini RM, Rezende SO. How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations [Internet]. Neural Computing and Applications. 2025 ; 37( Ja 2025): 1307-1319.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1007/s00521-024-10418-5 - Improving natural product knowledge extraction from academic literature with enhanced PDF text extraction and large language models
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Informações sobre o DOI: 10.1007/s00521-024-10418-5 (Fonte: oaDOI API)
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