TOWARDS COOPERATION AMONG COMPETITIVE TRADER AGENTS

Paulo André Lima de Castro, Jaime Simão Sichman

2007

Abstract

In order to manage their portfolios in stock markets, i.e., to determine buy and sell signals, human traders use a set of algorithms created by economists, which are based on stock prices series. These algorithms are usually referred as technical analysis. However, traders prefer to use a combination of several algorithms as indicators, rather than choosing a single one. The several signals provided are used to determine the trader order to buy or sell some stocks, or even to decide to not submit any order. In the last years, some researchers have tried to create new algorithms with learning skills in order to produce autonomous automatic traders, some of them using AI techniques. Inspired by the human traders´ decision processes, our architectural approach composes heterogeneous autonomous trader agents in a competitive multiagent system. This architecture allows the use of several algorithms, based on different technical analysis indexes to manage portfolios. We have implemented this architecture and we have performed a set of simulation experiments using real-data from NASDAQ stock market. The experimental results were compared to the performance of single agents playing alone, and a better global performance was observed when traders compete with each other for resources. These preliminary results indicate that competition among agents, as proposed here, may reach very good results, even among agents created to act alone in this kind of market.

References

  1. Decker, K., Pannu, A., Sycara, K., and Williamson, M. (1997). Designing behaviors for information agents. In Johnson, W. L. and Hayes-Roth, B., editors, Proceedings of the First International Conference on Autonomous Agents (Agents'97), pages 404-412, New York. ACM Press.
  2. Kearns, M. and Ortiz, L. (2003). The penn-lehman automated trading project. IEEE Intelligent System, 18(6):22-31.
  3. Sharpe, W. F. (1994). The sharpe ratio. Journal of Portfolio Management, 13(3):227-286.
  4. Sherstov, A. and Stone, P. (2004). Three automated stocktrading agents: A comparative study. In Proceedings of the Agent Mediated Electronic Commerce (AMEC) Workshop - AAMAS 2004 , New York.
  5. Subramanian, H., Ramamoorthy, S., Stone, P., and Kuipers, B. J. (2006). Designing safe, profitable automated stock trading agents using evolutionary algorithms. In GECCO 7806: Proceedings of the 8th annual conference on Genetic and evolutionary computation, pages 1777-1784, New York, NY, USA. ACM Press.
  6. Yahoo (2007). Yahoo http://finance.yahoo.com.
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Paper Citation


in Harvard Style

André Lima de Castro P. and Simão Sichman J. (2007). TOWARDS COOPERATION AMONG COMPETITIVE TRADER AGENTS . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 4: ICEIS, ISBN 978-972-8865-91-7, pages 138-143. DOI: 10.5220/0002388101380143


in Bibtex Style

@conference{iceis07,
author={Paulo André Lima de Castro and Jaime Simão Sichman},
title={TOWARDS COOPERATION AMONG COMPETITIVE TRADER AGENTS},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 4: ICEIS,},
year={2007},
pages={138-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002388101380143},
isbn={978-972-8865-91-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 4: ICEIS,
TI - TOWARDS COOPERATION AMONG COMPETITIVE TRADER AGENTS
SN - 978-972-8865-91-7
AU - André Lima de Castro P.
AU - Simão Sichman J.
PY - 2007
SP - 138
EP - 143
DO - 10.5220/0002388101380143