Abstract
The aim of the paper is to present an approach to support decision-making on financial markets using an idea of collective intelligence implemented as a multi-agent system, called A-Trader. A-Trader is integrated with the Meta Trader system which provides online data, including ticks of any securities, goods or currency pairs. Many of the implemented agents apply AI methods, communicate their trading advices to the supervisor that integrates all information and suggests the trading decision. The first part of the paper presents the architecture and functionalities of A-Trader. The structure and functionality of the agents and approach to the building of the trading strategies are detailed. The last section describes the results of the performance evaluation of selected trading strategies on FOREX.
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CITATION STYLE
Korczak, J., Hernes, M., & Bac, M. (2017). Collective Intelligence Supporting Trading Decisions on FOREX Market. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10448 LNAI, pp. 113–122). Springer Verlag. https://doi.org/10.1007/978-3-319-67074-4_12
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