Share This Article:

Evolutionary Algorithm Based Approach for Modeling Autonomously Trading Agents

Full-Text HTML Download Download as PDF (Size:560KB) PP. 45-54
DOI: 10.4236/iim.2014.62007    3,361 Downloads   4,788 Views Citations


The autonomously trading agents described in this paper produce a decision to act such as: buy, sell or hold, based on the input data. In this work, we have simulated autonomously trading agents using the Echo State Network (ESNs) model. We generate a collection of trading agents that use different trading strategies using Evolutionary Programming (EP). The agents are tested on EUR/ USD real market data. The main goal of this study is to test the overall performance of this collection of agents when they are active simultaneously. Simulation results show that using different agents concurrently outperform a single agent acting alone.

Cite this paper

Yaman, A. , Lucci, S. and Gertner, I. (2014) Evolutionary Algorithm Based Approach for Modeling Autonomously Trading Agents. Intelligent Information Management, 6, 45-54. doi: 10.4236/iim.2014.62007.

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.