Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach (2023)
- Authors:
- USP affiliated authors: LIANG, ZHAO - FFCLRP ; UEYAMA, JO - ICMC ; ZUÑIGA, ESTEBAN WILFREDO VILCA - ICMC ; RANIERI, CAETANO MAZZONI - ICMC
- Unidades: FFCLRP; ICMC
- DOI: 10.1016/j.procs.2023.08.192
- Subjects: DINHEIRO ELETRÔNICO; APRENDIZAGEM PROFUNDA; REDES COMPLEXAS; INVESTIMENTOS; LUCRO
- Keywords: Blockchain; Cryptocurrency forecasting
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- ISSN: 1877-0509
- Volume/Número/Paginação/Ano: v. 222, p. 539-548, 2023
- Conference titles: International Neural Network Society Workshop on Deep Learning Innovations and Applications - INNS DLIA
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by-nc-nd
-
ABNT
ZUÑIGA, Esteban Wilfredo Vilca et al. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.procs.2023.08.192. Acesso em: 28 dez. 2025. , 2023 -
APA
Zuñiga, E. W. V., Ranieri, C. M., Zhao, L., Ueyama, J., Zhu, Y. -tao, & Ji, D. (2023). Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. doi:10.1016/j.procs.2023.08.192 -
NLM
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192 -
Vancouver
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192 - A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions
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Informações sobre o DOI: 10.1016/j.procs.2023.08.192 (Fonte: oaDOI API)
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