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中国管理科学 ›› 2024, Vol. 32 ›› Issue (1): 23-30.doi: 10.16381/j.cnki.issn1003-207x.2021.0160

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具有灵活时间期限的混合投资组合优化模型

刘勇军(),伍健栋,张卫国   

  1. 华南理工大学工商管理学院,广东 广州 510641
  • 收稿日期:2021-01-22 修回日期:2021-11-29 出版日期:2024-01-25 发布日期:2024-02-08
  • 作者简介:刘勇军(1981-),男(汉族),湖南邵阳人,华南理工大学工商管理学院,教授,博士生导师,博士,研究方向:金融工程与风险管理,E-mail:yjlgx0202@126.com.
  • 基金资助:
    国家自然科学基金项目(71971086);广东省自然科学基金青年项目(2019B151502037);广东省青年珠江学者项目(粤教师函[2019]25号);中央高校基本科研业务费项目(2019ZD13)

Mixed Portfolio Optimization Model Within Flexible Time Horizon

Yongjun Liu(),Jiandong Wu,Weiguo Zhang   

  1. School of Business Administration,South China University of Technology,Guangzhou 510640,China
  • Received:2021-01-22 Revised:2021-11-29 Online:2024-01-25 Published:2024-02-08

摘要:

在经济全球化和金融一体化背景下,投资者资产配置需求变得越来越多元化。如何构建合理的多元化投资组合已成为金融理论研究的热点问题之一。为此,本文考虑由项目、股票及无风险资产组成的混合投资组合选择问题。假定在资产组合的投资期限由所选中项目执行期灵活确定的前提下,投资者同时考虑项目间依赖与排斥关系、交易成本及破产风险控制等现实因素,提出以终端财富净现值最大为目标的混合投资组合优化模型。然后,设计改进的多策略融合人工蜂群算法对所构建模型进行求解。最后,借助算例分析来阐明所提出模型的实用性及算法有效性。研究结果表明:灵活时间期限的混合投资组合策略较现有的灵活时间期限的项目投资组合策略更为有效。

关键词: 混合投资组合, 灵活时间期限, 人工蜂群算法, 现实因素

Abstract:

Under the background of economic globalization and financial integration, investors' asset allocation needs become more and more diversified. How to construct reasonable diversified portfolio strategy has become one of the hot issues in financial theory research. To this end, a mixed portfolio selection problem composed of project, stock and risk-free assets is considered. Assuming that the investment period of the portfolio is determined flexibly by the execution period of the selected project, the investors consider the real factors such as the dependence and exclusion relationship between the projects, the transaction cost and the bankruptcy risk control. A mixed portfolio optimization model with the objective of maximizing the net present value of terminal wealth is proposed. Then, an improved multi-strategy fusion artificial bee colony algorithm is designed to solve the proposed model. Finally, a numerical example is provided to illustrate the application of our model and demonstrate the effectiveness of the solution algorithm. The computational results show that the mixed portfolio investment strategy with flexible time horizon is more effective than the existing project portfolio investment strategy with flexible time horizon.

Key words: mixed portfolio, flexible time horizon, artificial bee colony algorithm, practical factors

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