张鹏, 黄梅雨, 彭壁玉. 具有机会约束的多阶段可信性M-AD投资组合优化[J]. 华南师范大学学报(自然科学版), 2019, 51(3): 94-102. doi: 10.6054/j.jscnun.2019050
引用本文: 张鹏, 黄梅雨, 彭壁玉. 具有机会约束的多阶段可信性M-AD投资组合优化[J]. 华南师范大学学报(自然科学版), 2019, 51(3): 94-102. doi: 10.6054/j.jscnun.2019050
ZHANG Peng, HUANG Meiyu, PENG Biyu. Multiperiod Mean-Absolute Deviation Credibilitic Portfolio Optimization with Chance Constraint[J]. Journal of South China Normal University (Natural Science Edition), 2019, 51(3): 94-102. doi: 10.6054/j.jscnun.2019050
Citation: ZHANG Peng, HUANG Meiyu, PENG Biyu. Multiperiod Mean-Absolute Deviation Credibilitic Portfolio Optimization with Chance Constraint[J]. Journal of South China Normal University (Natural Science Edition), 2019, 51(3): 94-102. doi: 10.6054/j.jscnun.2019050

具有机会约束的多阶段可信性M-AD投资组合优化

Multiperiod Mean-Absolute Deviation Credibilitic Portfolio Optimization with Chance Constraint

  • 摘要: 本文基于可信性理论,考虑交易成本、借贷约束、阈值约束和基数约束等现实约束,我们提出一种新的具有机会约束的多阶段可信性均值绝对偏差(M-AD)投资组合优化模型。该模型在给定的置信水平下,运用可信性均值和绝对偏差衡量资产的收益和风险,通过对终期财富的最优化实现投资者的预期收益。运用可信性理论,该模型被转化为确定型的动态优化问题。由于交易成本和基数约束的存在,该模型为具有路径依赖的混合整数动态优化问题。文章提出一种新的前向动态规划方法求解。最后,文章通过实证研究验证了模型和算法的有效性。

     

    Abstract: In this paper, we propose a new multiperiod credibilitic portfolio selection model with fuzzy chance constraint, which the real constraints, ie. the borrowing constraints, threshold constraints, cardinality constraints and transaction costs are considered. We use credibilitic mean and credibilitic absolute deviation to measure return and risk of portfolio selection, respectively. Under the given confidence level, the return of portfolio selection cant be less than preset value. Based on credibilitic theories, the model is transformed into a dynamic optimization problem. Because of the transaction costs and cardinality constraints, the model is a mix integer dynamic optimization problem with path dependence, which is NP hard problem that is difficult to handle. A novel forward dynamic programming method is designed to obtain the optimal portfolio strategy. At last, numerical experiments are included to showcase the applicability and efficiency of the model in a real investment environment.

     

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