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A Step-By-Step Implementation of a Multi-Agent Currency Trading System

A Step-By-Step Implementation of a Multi-Agent Currency Trading System

Rui Pedro Barbosa, Orlando Belo
Copyright: © 2011 |Pages: 41
ISBN13: 9781609601713|ISBN10: 1609601718|EISBN13: 9781609601737
DOI: 10.4018/978-1-60960-171-3.ch014
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MLA

Barbosa, Rui Pedro, and Orlando Belo. "A Step-By-Step Implementation of a Multi-Agent Currency Trading System." Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications, edited by Goran Trajkovski, IGI Global, 2011, pp. 213-253. https://doi.org/10.4018/978-1-60960-171-3.ch014

APA

Barbosa, R. P. & Belo, O. (2011). A Step-By-Step Implementation of a Multi-Agent Currency Trading System. In G. Trajkovski (Ed.), Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications (pp. 213-253). IGI Global. https://doi.org/10.4018/978-1-60960-171-3.ch014

Chicago

Barbosa, Rui Pedro, and Orlando Belo. "A Step-By-Step Implementation of a Multi-Agent Currency Trading System." In Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications, edited by Goran Trajkovski, 213-253. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-171-3.ch014

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Abstract

With this chapter the authors intend to demonstrate the potential practical use of intelligent agents as autonomous financial traders. The authors propose an architecture to be utilized in the creation of this type of agents, consisting of an ensemble of classification and regression models, a case-based reasoning system and an expert system. This architecture was used to implement six intelligent agents, each being responsible for trading one of the following currency pairs with a 6-hour timeframe: CHF/JPY, EUR/CHF, EUR/JPY, EUR/USD, USD/CHF and USD/JPY. These agents simulated trades during an out-of-sample period going from February of 2007 till July of 2010, having all achieved an acceptable performance. However, their strategies resulted in relatively high drawdowns, and much of their profit disappeared once the trading costs were factored into the trading simulation. In order to overcome these problems, they integrated the agents in a multi-agent system, in which agents communicate their decisions to each other before sending the market orders, and work together to eliminate redundant trades. This system averaged out the returns of the agents, thus eliminating much of the risk associated with their individual trading strategies, and also originated considerable savings in trading expenses. Their results seem to vindicate the usefulness of the proposed trading agent architecture, and also demonstrate that there is indeed a place for intelligent agents in financial markets.

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