Evaluation of Technical Analysis Trading Rules in a Artificial Stock Market Environment

Authors

Keywords:

Multi-agent System, Artificial Stock Market, Heterogeneous Agents, Performance Technical Trading Rules

Abstract

Artificial multi-agent systems can be applied to replicate complex processes, including the stock market. In this manuscript, an artificial stock market was simulated. Heterogeneous agents are set to trade by using different investiment strategies through a double auction market. The main innovative aspect of this work is to evaluate the performance and effectiveness of agents with different investment strategies based on the combination of Technical/Fundamental Analysis. According to the simulations performed, the results showed that the time series resulting from the interactions among these agents resemble to the real financial series, reproducing some of the stylized facts found in the Literature. Moreover, the statistical analysis reported no significant differences in the distribution mean performance between these diverse agents types

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Author Biographies

Marcos Vinicius Lopes Pereira, Federal University of Sao João del-Rei

Possui graduação em Engenharia de Controle e Automação pela Universidade Federal de Minas Gerais (UFMG) concluída em 2003. Possui Mestrado em Engenharia Elétrica (UFMG), concluído em 2006, e Doutorado em Finanças/Administração (UFMG), concluído em 2020. Desde 2013 é Professor da Universidade Federal de São João del-Rei, Campus Alto Paraopeba, onde atua nos cursos de Engenharia Mecatrônica e Engenharia de Telecomunicações. Tem interesses relativos a pesquisas em finanças (teoria dos portfólios e análises de séries financeiras); modelagem e controle de sistemas dinâmicos; e inteligência computacional.

Michel Carlo Rodrigues Leles, Federal University of São João del-Rei

Possui graduação em Engenharia de Controle e Automação pela Universidade Federal de Minas Gerais (UFMG). Possui Mestrado e Doutorado em Engenharia Elétrica, também pela UFMG. Desde 2010 é Professor da Universidade Federal de São João del-Rei, Campus Alto Paraopeba, lotado no Departamento de Tecnologia. Sua pesquisa tem enfoque na grande área de Data Science, especialmente incluindo ferramentas de inteligência artificial, análise de séries temporais, processamento de sinais e finanças computacionais.

Robert Aldo Iquiapaza, Federal University of Minas Gerais

Possui graduação em Economia pela Universidad Nacional de San Agustín (UNSA). Possui Mestrado e Doutorado em Finanças/Administração pela Universidade Federal de Minas Gerais (UFMG). Desde 2010 é Professor da UFMG, onde atua principalmente nos cursos de graduação em Controladoria e Finanças e Administração; e nos cursos de mestrado/doutorado em Administração e Controladoria e Contabilidade. Tem interesse de pesquisas em finanças corporativas, mercado de capitais e financeiros, modelos econométricos, séries financeiras, modelagem e simulação computacional.

Elton Felipe Sbruzzi, Instituto Tecnológico de Aeronáutica

PhD em Finanças Computacionais pela Univeristy of Essex, UK. Mestre em Economia pela Universidade Federal do Rio Grande do Sul. Graduado em Economia pela Universidade Estadual de Campinas. Professor Adjunto na Divisão de Ciência da Computação do Instituto Tecnológico de Aeronáutica, desde 2018. Desenvolve pesquisa interdisciplinar abrangendo a aplicação de Ciência de Dados e Inteligência Artificial em várias áreas do conhecimento.

Cairo Lucio Nascimento Júnior, Instituto Tecnológico de Aeronáutica

Possui graduação em Engenharia Elétrica pela Universidade Federal de Uberlândia, mestrado em Engenharia Eletrônica e Computação pelo Instituto Tecnológico de Aeronáutica (ITA) e doutorado em Engenharia Elétrica e Eletrônica pela University of Manchester Institute of Science and Technology, Control Systems Centre, UK. Atua como professor no ITA, Divisão de Engenharia Eletrônica, Departamento de Sistemas e Controle, desde 1986. Tem experiência na área de Engenharia Elétrica, com ênfase em Controle de Sistemas Dinâmicos e na aplicação de técnicas de inteligência computacional para o desenvolvimento de soluções para problemas reais.

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Published

2021-03-09

How to Cite

Lopes Pereira, M. V. L., Leles, M. C. R., Iquiapaza, R. A., Sbruzzi, E. F., & Nascimento Júnior, C. L. (2021). Evaluation of Technical Analysis Trading Rules in a Artificial Stock Market Environment. IEEE Latin America Transactions, 18(10), 1707–1714. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/3296

Issue

Vol. 18 No. 10 (2020): Ordinary Issue

Section

Articles