Simulation of Financial Market with Buying and Selling Optimized by Particle Swarm

Authors

DOI:

https://doi.org/10.5902/2179460X40010

Keywords:

Financial market, Optimization, Particle swarm optimization, Computational simulation, Dynamics systems

Abstract

It has been of great interest, both on the part of researchers and investors, to define negotiation rules that make it possible to capture the dynamics of the financial markets. This article presents a negotiation model among financial agents, based on the stock buying and selling process, that form a financial market. For the adaptation of economic agents to the market, a Particle Swarm Optimization (PSO) algorithm was implemented to optimize trading rules between agents aiming at maximizing gains in the market. Times series of artificial markets and real Bovespa brazillian market, descripted by the index Bovespa, were used in the computational simulations. Through the simulations, the dynamics of the interaction of buying and selling between financial agents was explored. The results show that there is a dependence on the gains of the agents in the markets in relation to the trading strategies adopted. On the other hand, in the low markets this dependence was not observed, since no statistically significant differences were found for the amount of wealth accumulated among the market participants. For the Bovespa market, from the sell and purchase thresholds of the trades carried out, the agents that have the best strategies in the negotiations were identified.

Author Biographies

Kerolly Kedma Felix do Nascimento, Universidade Federal Rural de Pernambuco

Graduada em Matemática (Licenciatura). Mestre em Biometria e Estatística Aplicada. Atualmente é aluna do Doutorado em Biometria e Estatística Aplicada da Universidade Federal Rural de Pernambuco.

Jader da Silva Jale, Universidade Federal Rural de Pernambuco, Recife, PE

Possui Bacharelado em Estatística, Mestrado e Doutorado em Biometria e Estatística Aplicada e Pós-Doutorado em Ciência da Computação, todos pela Universidade Federal Rural de Pernambuco. Atualmente é professor Adjunto A e membro titular da Comissão de Pesquisa no Departamento de Estatística e Informática na Universidade Federal Rural de Pernambuco.

Tiago Alessandro Espínola Ferreira, Universidade Federal Rural de Pernambuco, Recife, PE

Possui graduação (Bacharelado) e mestrado em Física, tem doutorado em Ciências da Computação pela Universidade Federal de Pernambuco e pós-doutorado pela Harvard University e professor visitante do Institutee for Applied Computational Science at Harvard Jhon A. Paulson School of Engineering and Appied Sciences. Atualmente é professor associado, fundadores do Programa de Pós-graduação em Informática Aplicada e  membro permanente do Programa de Pós-Graduação em Biometria e Estatística Aplicada da Universidade Federal Rural de Pernambuco.

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Published

2021-03-10

How to Cite

Nascimento, K. K. F. do, Jale, J. da S., & Ferreira, T. A. E. (2021). Simulation of Financial Market with Buying and Selling Optimized by Particle Swarm. Ciência E Natura, 43, e21. https://doi.org/10.5902/2179460X40010