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

doi:10.12052/gdutxb.200071

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基于模糊收益率的分散化投资组合调整策略

综合研究 | 更新时间：2026-05-27

- 基于模糊收益率的分散化投资组合调整策略
- A Diversified Portfolio Selection Strategy Based on Fuzzy Return Rate
- 广东工业大学学报 2020年37卷第5期页码：13-21
- 作者机构：
  
  广东工业大学管理学院,广东,广州,510520
- 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
- 基金信息：
  
  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)
- DOI：10.12052/gdutxb.200071
  中图分类号： F830
- 网络首发：2020-09-17，
  
  纸质出版：2020
- 稿件说明：
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杨兴雨, 刘伟龙, 井明月, 张永. 基于模糊收益率的分散化投资组合调整策略[J]. 广东工业大学学报, 2020, 37(5): 13-21.

Yang Xing-yu, Liu Wei-long, Jing Ming-yue, et al. A Diversified Portfolio Selection Strategy Based on Fuzzy Return Rate[J]. 2020, 37(5): 13-21.
杨兴雨, 刘伟龙, 井明月, 张永. 基于模糊收益率的分散化投资组合调整策略[J]. 广东工业大学学报, 2020, 37(5): 13-21. DOI： 10.12052/gdutxb.200071.

Yang Xing-yu, Liu Wei-long, Jing Ming-yue, et al. A Diversified Portfolio Selection Strategy Based on Fuzzy Return Rate[J]. 2020, 37(5): 13-21. DOI： 10.12052/gdutxb.200071.

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。

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.

关键词

Keywords

references

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