序贯非负最小方差模型平均组合及应用

Combined Portfolios from Sequentially Non-negative Minimum Variance Model and Its Application

研究目标:构建改进全局非负最小方差模型的序贯最小方差模型平均组合。研究方法:在大样本下,给出序贯非负最小方差模型组合的期望方差和收益的理论近似,在此基础上探讨其平均组合的期望收益和期望方差的性质,并通过数值模拟和沪深300成分股数据在有限样本下进行验证。研究发现:与全局非负最小方差模型组合相比,序贯非负最小方差模型平均组合在样本外风险更小、收益更高,且保持组合稀疏性。研究创新:在卖空限制下,给出了一种比全局非负最小方差模型更优的组合构建方法。研究价值:序贯非负最小方差模型平均组合方法在国内市场具有较强的适用性,同时丰富了目前投资组合方法论的研究。

Research Objectives:This paper improves the non-negatively global minimum-variance model and proposes the sequentially non-negative minimum-variance model.Research Methods:We establish the asymptotic properties of the estimates for the sequentially non-negative minimum variance model and then analysis the properties of the expected return and variance of the combined portfolio from the sequential model.These properties are verified through simulation and the history data analysis.Research Findings:Compared with the non-negatively global minimum-variance portfolio,the proposed combined portfolio has lower out-of-sample risk and higher return.In the meanwhile,the proposed method also has an advantage of generating a sparse portfolio.Research Innovations:Under the no-short sell constraint,this paper proposes a novel combined portfolio by sequentially non-negative minimum-variance models.Research Value:The proposed method shows strong applicability in Chinese stock market and this work enriches the current research on modern portfolio theory.