广东工业大学学报 ›› 2020, Vol. 37 ›› Issue (05): 13-21.doi: 10.12052/gdutxb.200071

• 综合研究 • 上一篇    下一篇

基于模糊收益率的分散化投资组合调整策略

杨兴雨, 刘伟龙, 井明月, 张永   

  1. 广东工业大学 管理学院，广东 广州 510520
  • 收稿日期:2020-05-19 出版日期:2020-09-17 发布日期:2020-09-17
  • 作者简介:杨兴雨(1981-)，男，教授，博士，主要研究方向为金融工程与在线金融算法
  • 基金资助:
    国家自然科学基金资助项目(71501049)；教育部人文社会科学研究基金资助项目(18YJA630132)

A Diversified Portfolio Selection Strategy Based on Fuzzy Return Rate

Yang Xing-yu, Liu Wei-long, Jing Ming-yue, Zhang Yong   

  1. School of Management, Guangdong University of Technology, Guangzhou 510520, China
  • Received:2020-05-19 Online:2020-09-17 Published:2020-09-17

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摘要： 投资组合选择是量化金融领域的核心问题之一。本文研究模糊环境下考虑交易费用和基数约束的分散化投资组合调整问题。首先，将风险资产的收益率视为模糊变量，通过建立一个模糊收益率拟合模型，确定了各资产收益率的模糊分布。其次，通过提出一个新的分散化测度，建立了模糊均值-下半方差-分散化投资组合调整模型。然后，设计了一个改进的遗传算法对模型进行求解。最后，选取真实的股票数据进行实例分析。结果表明所提出的策略优于传统的投资组合调整策略。

关键词: 模糊投资组合模型, 模糊收益率拟合, 分散化测度, 改进的遗传算法

Abstract: Portfolio selection is one of the core issues in the field of quantitative finance. A diversified portfolio selection strategy is proposed by considering transaction cost and cardinality constraint. Firstly, the return rates of risky assets are regarded as fuzzy numbers and a fuzzy return rate fitting model is proposed to determine the fuzzy distribution of the assets’ return rates. Then, a new diversification measure is proposed for the portfolio and a fuzzy mean-semi-variance-diversification portfolio selection model is established. Next, a modified genetic algorithm is designed to solve the proposed models. Finally, an empirical example with real stock data is used to illustrate the proposed strategy. The results show that the proposed strategy performs better than the conventional portfolio selection strategies.

Key words: fuzzy portfolio model, fuzzy return rate fitting, diversification measure, modified genetic algorithm

中图分类号: 

  • F830
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