Consensus-based trading strategy in a-trader system

• Authors: Jerzy Korczak , Marcin Hernes , Maciej Bac
• Languages of publication: EN

Abstracts

EN

The authors of this paper present an approach to trading strategy design for an A-Trader multi-agent system which supports investment decisions on the stock market. The functionalities of the system, and the main component, the Supervisor Agent, used as a strategy a consensus method to reduce the level of investment risk, are described. The consensus method allows the coordination of the work of agents, and on the basis of the decisions provided by the agents presents trading advice to the investor. The strategy has been tested on FOREX quotes, namely on the pair USD/PLN. The results of the research are described and the directions of the further development of the platform are provided in the conclusion.

Keywords

EN

multi-agent systems; financial decisions; consensus method; A-Trader system

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Informatyka Ekonomiczna
• Year: 2013
• Issue: 3(29)
• Pages: 98-110

Contributors

author

Jerzy Korczak

• Wroclaw University of Economics

author

Marcin Hernes

• Wroclaw University of Economics

author

Maciej Bac

• Wroclaw University of Economics

References

• Barbosa R.P., Belo O., Multi-Agent Forex Trading System, [in:] Agent and Multi-Agent Technology for Internet and Enterprise Systems, “Studies in Computational Intelligence” 2010, vol. 289, pp. 91-118.
• Chan L., Wk Wong A., Automated trading with genetic-algorithm neural-network risk cybernetics: An application on FX Markets, “Finamatrix”, January 2011, pp. 1-28.
• Dempster M., Jones C., A real time adaptive trading system using genetic programming, “Quantitative Finance” 2001, 1, pp. 397-413.
• Hernes M., Metody consensusu w rozwiązywaniu konfliktów wiedzy w wieloagentowym systemie wspomagania decyzji, Uniwersytet Ekonomiczny we Wrocławiu, Wrocław 2011.
• Hernes M., Nguyen N.T., Deriving consensus for hierarchical incomplete ordered partitions and coverings, “Journal of Universal Computer Science” 2007, 13(2), pp. 317-328.
• Jajuga K., Jajuga T., Inwestycje: instrumenty finansowe, ryzyko finansowe, inżynieria finansowa, Wydawnictwo Naukowe PWN, Warszawa 2000.
• Karjalainen R., Using genetic algorithms to find technical trading rules, “Journal of Financial Economics” 1999, 51, pp. 245-271.
• Korczak J., Lipinski P., Systemy agentowe we wspomaganiu decyzji na rynku papierów wartościowych, [in:] Rozwój informatycznych systemów wieloagentowych w środowiskach społeczno-gospodarczych, ed. S. Stanek et al., Placet, Warszawa 2008, pp. 289-301.
• Korczak J., Bac M., Drelczuk K., Fafuła A., A-Trader − Consulting agent platform for stock exchange gamblers, [in:] Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), Wrocław 2012, pp.963-968.
• Korczak J., Hernes M., Bac M., Risk avoiding strategy in multi-agent trading system, [in:] Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), Kraków 2013 (in press).
• LeBaron B., Active and passive learning in agent-based financial markets, “Eastern Economic Journal” 2011, vol. 37, pp. 35-43.
• Nguyen N.T., Using consensus methodology in processing inconsistency of knowledge, [in:] Advances in Web Intelligence and Data Mining, series: Studies in Computational Intelligence, ed. M. Last et al., Springer-Verlag, 2006, pp. 161-170.
• Sobieska-Karpińska J., Hernes M., Consensus determining algorithm in multiagent decision support system with taking into consideration improving agent’s knowledge, [in:] Proceedings of the Federated Conference on Computer Science and Information Systems (FedCSIS), Wrocław 2012, pp. 1035-1040.
• Zgrzywa M., Consensus determining with dependencies of attributes with interval values, “Journal of Universal Computer Science” 2007, vol. 13, no. 2, pp. 329-344.