张鹏, 李欣茵, 曾永泉. 基本指数-最小下半方差投资组合优化研究[J]. 华南师范大学学报(自然科学版), 2021, 53(3): 93-101. doi: 10.6054/j.jscnun.2021047
引用本文: 张鹏, 李欣茵, 曾永泉. 基本指数-最小下半方差投资组合优化研究[J]. 华南师范大学学报(自然科学版), 2021, 53(3): 93-101. doi: 10.6054/j.jscnun.2021047
ZHANG Peng, LI Xinyin, ZENG Yongquan. The Mixture of Fundamental Indexing and Minimum Semi-variance Portfolio Selection[J]. Journal of South China Normal University (Natural Science Edition), 2021, 53(3): 93-101. doi: 10.6054/j.jscnun.2021047
Citation: ZHANG Peng, LI Xinyin, ZENG Yongquan. The Mixture of Fundamental Indexing and Minimum Semi-variance Portfolio Selection[J]. Journal of South China Normal University (Natural Science Edition), 2021, 53(3): 93-101. doi: 10.6054/j.jscnun.2021047

基本指数-最小下半方差投资组合优化研究

The Mixture of Fundamental Indexing and Minimum Semi-variance Portfolio Selection

  • 摘要: 为了克服方差作为风险度量无法区分收益和损失的局限性,同时弥补经典均值-方差模型忽略了企业基本面状况的缺陷,该文结合下半方差和基本指数的优点,分别考虑1-、2-范数交易成本,构建了基于期望效用最大化的基本指数-最小下半方差投资组合模型(简称“FI-semiv模型”),并运用不等式组的旋转算法进行求解. 文章通过“滚动窗口”的方法,对FI-semiv模型进行了样本外检验与分析,并进一步将该模型与最小方差模型、最小下半方差模型和等比例投资模型的夏普比率进行对比. 结果表明:基于FI-semiv模型构建的投资组合的夏普比率得到了有效提高,FI-semiv投资组合的风险更小,投资效率更高.

     

    Abstract: In order to overcome the limitation of variance in distinguishing income and loss and solve the problem caused by ignoring the fundamentals in MV model, a mixture of Fundamental Indexing and minimum semi-variance portfolio ("FI-semiv"model), taking into consideration 1- and 2-norm transaction costs respectively and aiming to maximize the expected utility of investors, is proposed and solved with the pivoting algorithm. The model is a convex quadratic programming problem with linear equality and inequality constraints. Based on the "rolling sample" approach, the out-of-sample sharp ratios of different models are compared. It turns out that the sharp ratio of the FI-semiv portfolio has been effectively improved, which means that the portfolio is less risky and more efficient.

     

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