Forecasting financial market structure from network features using machine learning (2024)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; BRAZ, DOUGLAS DONIZETI DE CASTILHO - ICMC
- Unidade: ICMC
- DOI: 10.1007/s10115-024-02095-6
- Subjects: APRENDIZADO COMPUTACIONAL; PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS); REDES COMPLEXAS; MERCADO FINANCEIRO
- Keywords: Financial networks; Network link prediction; Information filtering networks; Correlation-based networks; Stock markets
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Knowledge and Information Systems
- ISSN: 0219-1377
- Volume/Número/Paginação/Ano: In press
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
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ABNT
CASTILHO, Douglas et al. Forecasting financial market structure from network features using machine learning. Knowledge and Information Systems, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10115-024-02095-6. Acesso em: 10 jun. 2024. -
APA
Castilho, D., Souza, T. T. P., Kang, S. M., Gama, J., & Carvalho, A. C. P. de L. F. de. (2024). Forecasting financial market structure from network features using machine learning. Knowledge and Information Systems. doi:10.1007/s10115-024-02095-6 -
NLM
Castilho D, Souza TTP, Kang SM, Gama J, Carvalho ACP de LF de. Forecasting financial market structure from network features using machine learning [Internet]. Knowledge and Information Systems. 2024 ;[citado 2024 jun. 10 ] Available from: https://doi.org/10.1007/s10115-024-02095-6 -
Vancouver
Castilho D, Souza TTP, Kang SM, Gama J, Carvalho ACP de LF de. Forecasting financial market structure from network features using machine learning [Internet]. Knowledge and Information Systems. 2024 ;[citado 2024 jun. 10 ] Available from: https://doi.org/10.1007/s10115-024-02095-6 - The strength of influence ties in stock networks: empirical analysis for portfolio selection
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Informações sobre o DOI: 10.1007/s10115-024-02095-6 (Fonte: oaDOI API)
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