| 考虑复杂约束的鲁棒均值-CVaR投资组合模型及粒子群算法 |
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| 引用本文： | 李军,周建力. 考虑复杂约束的鲁棒均值-CVaR投资组合模型及粒子群算法[J]. 控制与决策, 2016, 31(12): 2219-2224 |
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| 作者姓名： | 李军 周建力 |
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| 作者单位： | 电子科技大学经济与管理学院,成都611731,电子科技大学经济与管理学院,成都611731 |
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| 基金项目： | 国家自然科学基金项目(71571031)；中央高校基本科研业务费专项资金项目(ZYGX2013J133) |
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| 摘 要： | 投资组合模型中期望收益等参数的估计误差对最优投资组合策略的稳定性产生重要影响. 在提出考虑复杂约束和交易成本的鲁棒均值-CVaR投资组合模型的基础上, 设计改进粒子群算法来求解该模型. 应用实际交易数据对所提出的模型和算法进行数值实验和比较, 结果表明改进粒子群算法能有效地求解该模型, 产生更稳定的最优投资策略, 从而能够更好地适合实际投资环境.
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| 关 键 词： | 鲁棒优化 投资组合 条件风险价值 复杂约束 粒子群算法 |
| 收稿时间： | 2015-09-13 |
| 修稿时间： | 2015-09-13 |
Robust mean-CVaR portfolio selection model with complicated realistic constraints and its improved particle swarm optimization algorithm |
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| LI Jun and ZHOU Jian-li. Robust mean-CVaR portfolio selection model with complicated realistic constraints and its improved particle swarm optimization algorithm[J]. Control and Decision, 2016, 31(12): 2219-2224 |
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| Authors: | LI Jun and ZHOU Jian-li |
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| Affiliation: | School of Management and Economics,University of Electronic Science and Technology of China,Chengdu 611731,China. and School of Management and Economics,University of Electronic Science and Technology of China,Chengdu 611731,China. |
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| Abstract: | Errors in the estimation of expected return of securities of portfolio selection models may have large effect on the stability of optimal strategy. A robust portfolio selection model with complicated realistic constraints is proposed. Then an improved particle swarm optimization is proposed to solve the model. The empirical analysis and comparisons from the real market data indicate that the proposed improved particle swarm optimization algorithm can solve the proposed model more efficiently, and the proposed model obtains more stable optimal portfolio strategy. |
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