An automated decision-making system employing complex networks and blockchain for the decentralized stock market

Autor(es)

Garcia, Rodrigo Dutra ; Ferreira, Junio Cesar ; Zanotti, Lucas ; Ramachandran, Gowri ; Estrella, Julio Cezar ; Ueyama, Jo

• Tipo de documento: Artigo Científico
• Fonte: EXPERT SYSTEMS WITH APPLICATIONS; v. 257, p. 12-pg., 2024-08-20.

Resumo

Stock markets are inherently complex, posing a challenge for investors who must analyze large amounts of data for strategic decision-making. This complexity, coupled with the centralized control and high transaction costs of traditional stock market systems, highlights the need for strategies that simplify analysis and promote informed, cost-effective investment choices. To address this issue, this work proposes real-time decision-making support for the stock market. The system leverages complex networks to enable a deeper understanding and analysis of intricate market trends and behaviors. It also integrates blockchain technology to decentralize traditional stock market infrastructures, reducing transaction costs and increasing transparency for user transactions and asset exchanges. Our system leverages complex networks to analyze multi-source marketplace data, operating on a cloud-computing infrastructure. This approach simplifies the analysis of intricate market dynamics. We evaluated our proof-of-concept prototype using real-world NASDAQ stock market data, demonstrating its ability to aid investor decision-making and enable decentralized transactions with minimal overhead. (AU)

• Processo FAPESP: 23/15919-1 - Investigando Estratégias de Segurança e Privacidade em Redes 6G por meio de Mecanismos de Governança Baseados em Blockchain
• Beneficiário: Rodrigo Dutra Garcia
• Modalidade de apoio: Bolsas no Brasil - Doutorado