广东工业大学学报 ›› 2020, Vol. 37 ›› Issue (04): 59-64.doi: 10.12052/gdutxb.190091

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基于活跃专家意见的在线投资组合策略

何锦安, 王蓓, 林家星   

  1. 广东工业大学 管理学院，广东 广州 510520
  • 收稿日期:2019-07-05 出版日期:2020-07-11 发布日期:2020-07-02
  • 通信作者: 王蓓(1974-)，女，讲师，博士，主要研究方向为决策科学，E-mail：linda@gdut.edu.cn E-mail:linda@gdut.edu.cn
  • 作者简介:何锦安(1993-)，男，硕士研究生，主要研究方向为在线金融决策
  • 基金资助:
    教育部人文社会科学研究基金资助项目(18YJA630132)

An Online Portfolio Strategy Based on Active Expert Advice

He Jin-an, Wang Bei, Lin Jia-xing   

  1. School of Management, Guangdong University of Technology, Guangzhou 510520, China
  • Received:2019-07-05 Online:2020-07-11 Published:2020-07-02

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摘要： 综合考虑专家意见是投资者常用的投资决策方法。通过集成活跃专家意见, 提出了一个新的在线投资组合策略。首先将所有定常再调整策略看作专家, 并通过淘汰近期表现最差的专家构造活跃专家集合; 然后利用弱集成算法集成所有活跃专家的意见, 进而构造弱集成活跃专家策略。采用实际的股票数据对提出的策略进行数值分析, 结果表明该策略具有更好的竞争性能。

关键词: 在线投资组合, 活跃专家意见, 弱集成算法, 移动窗口, 在线学习

Abstract: It is a common investment decision-making method for investors to comprehensively consider expert advice. By aggregating active expert advice, a new online portfolio strategy is proposed. First, considering all constant rebalanced portfolio strategies as experts, an active expert set is constructed by eliminating the worst recent performing expert. Second, using the weak aggregating algorithm to aggregate all active expert advice, an online portfolio strategy is then constructed. The proposed strategy is numerically analyzed by using actual stock data. The results show that the strategy has a more competitive performance.

Key words: online portfolio, active expert advice, weak aggregating algorithm, moving window, online learning

中图分类号: 

  • F830.59
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[1] 杨兴雨, 何锦安, 沈健华. 基于移动窗口的适应性在线投资组合策略[J]. 广东工业大学学报, 2018, 35(03): 61-66.
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