Advanced search
Start date

Employing computational intelligence techniques and Big Data analytics in a multi-agent system experiment of finance

Grant number: 17/20248-8
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): December 01, 2017
Effective date (End): May 31, 2019
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Cairo Lúcio Nascimento Júnior
Grantee:Michel Carlo Rodrigues Leles
Host Institution: Divisão de Engenharia Eletrônica (IEE). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil
Associated research grant:16/04992-6 - Employing computational intelligence techniques and Big Data analytics in a multi-agent system experiment of finance, AP.ESCIENCE.R


We propose a research within the Agent-Based Computational Finance area. This area has been studying the application of multi-agent system models and computational intelligence techniques in finance. In this context, we intend to employ different computational intelligence techniques (reinforcement learning, genetic algorithm and fuzzy logic) and big data analytics in a multi-agent system experiment (agent-based model simulation of a double auction market) of finance. The research aims are to investigate of the ability of reinforcement learning to model the agents learning and evolution process in the financial markets, to study the use of multi-criteria performance indexes in order to model the agent learning process, and to analyse the consequence of this agents' behaviour to the financial markets as a whole. Our plan is the introduction of different computational intelligence techniques in an agent-based model simulation of the financial market, and the test of a list of hypotheses about the agents and the financial markets micro-structure. This research is relevant because its outcome can help researchers, financial regulators, policymakers and practitioners to better understand the agents learning and evolution process, and its consequences to the financial market micro-structure as a whole. We are requesting fellowships for one postdoctoral researcher with expertise in Computational Finance. In terms of internationalization, this research has an international collaboration with the Institute for Analytics and Data Science and the School of Computer Science and Electronic Engineering of the University of Essex, UK. As a part of this project, we intend to intensify our relationship though a series of researchers' visits and interchange.

News published in Agência FAPESP Newsletter about the scholarship:
Articles published in other media outlets (0 total):
More itemsLess items

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
RODRIGUES LELES, MICHEL CARLO; MOZELLI, LEONARDO AMARAL; SBRUZZI, ELTON FELIPE; NASCIMENTO JUNIOR, CAIRO LUCIO; GUIMARAES, HOMERO NOGUEIRA. A Multicriteria Trading System Based on Singular Spectrum Analysis Trading Rules. IEEE SYSTEMS JOURNAL, v. 14, n. 1, p. 1468-1478, . (16/04992-6, 17/20248-8)
LELES, MICHEL C. R.; MOREIRA, MARIANA G.; VALE-CARDOSO, ADRIANO S.; NASCIMENTO JUNIOR, CAIRO L.; SBRUZZI, ELTON F.; GUIMARAES, HOMERO N.. Comparison between Basic and Toeplitz SSA applied to non-stationary time-series. STATISTICS AND ITS INTERFACE, v. 12, n. 4, p. 527-536, . (16/04992-6, 17/20248-8)
RODRIGUES LELES, MICHEL CARLO; MOZELLI, LEONARDO AMARAL; NASCIMENTO JUNIOR, CAIRO LUCIO; SBRUZZI, ELTON FELIPE; GUIMARAES, HOMERO NOGUEIRA. Study on Singular Spectrum Analysis as a New Technical Oscillator for Trading Rules Design. FLUCTUATION AND NOISE LETTERS, v. 17, n. 4, . (16/04992-6, 17/20248-8)

Please report errors in scientific publications list by writing to: