基于Agent的遗传算法，采用金融技术分析，利用历史股票市场数据进行交易决策

Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004). Pub Date : 2004-09-20 DOI:10.1109/IAT.2004.23

C. Schoreels, B. Logan, J. Garibaldi

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引用次数: 31

摘要

本文研究了一个基于代理的交易系统的有效性。该系统采用一种简单的遗传算法，为每个经纪人进化出一种优化的交易方法，他们的交易决策基于一系列产生交易信号的技术指标。他们的交易模式遵循一个简单的适应度函数，即在每个进化周期中使净资产最大化。他们的表现被与指数所代表的市场走势以及由人类专业人士管理的投资基金进行比较，以建立一个相对的成功衡量标准。结果表明，尽管这些代理人在本质上相当原始，但在不同的市场环境中，发达系统的表现与人类同行相当。未来即将开展的工作将进一步完善和探索这种方法的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Agent based genetic algorithm employing financial technical analysis for making trading decisions using historical equity market data

This work investigates the effectiveness of an agent based trading system. The system developed employs a simple genetic algorithm to evolve an optimized trading approach for every agent, with their trading decisions based on a range of technical indicators generating trading signals. Their trading pattern follows a simple fitness function of maximizing net assets for every evolutionary cycle. Their performance is analyzed compared to market movements as represented by its index, as well as investment funds run by human professionals to establish a relative measure of success. The results show that the developed system performs comparably to its human counterparts across different market environments, despite these agents being rather primitive in nature. Future forthcoming work refines and explores the potential of this approach further.

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Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).

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