阈值约束组合选择的多智能体模型

Ritesh Kumar, Subir Bhattacharya
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引用次数: 0

摘要

本文提出了一个投资组合选择问题的多智能体模型,其中每只被选择的股票至少占总投资的指定比例。一个代理系统划分初始财富,并遵循从伪随机投资组合开始的个人投资组合调整策略。这些代理定期分享他们的业绩信息,并利用其他代理报告的经验改变投资组合的组成。最终的阈值约束组合是通过整合代理人根据股票的过去表现得出的单个投资组合来构建的。在实际市场中,基于agent的模型建议的投资组合往往优于均值方差模型建议的投资组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-agent model for threshold constrained portfolio selection
This paper presents a multi-agent model for the portfolio selection problem where every selected stock would have at least a specified fraction of the total investment. A system of agents divides the initial wealth and follows individual portfolio adjustment strategies starting with pseudo-random portfolios. Periodically, the agents share information about their performances, and change the composition of the portfolios leveraging experiences reported by other agents. A final threshold constrained portfolio is constructed by consolidating individual portfolios arrived at by the agents based on the past performance of the stocks. The portfolio suggested by the agent based model frequently outperforms the portfolios suggested by mean-variance models when tried out in real market.
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