考虑背景风险的均值-半方差投资组合优化模型

在投资决策过程中，投资者不仅面临金融市场风险，还将面临金融资产价格波动以外的背景风险.针对现有考虑背景风险投资组合模型大部分都是以方差作为风险度量的不足，本文用半方差代替方差作为风险度量，研究同时考虑金融市场风险和背景风险的投资组合选择问题，提出考虑背景风险的均值-半方差投资组合优化模型.然后，给出临界线算法对所构建的模型进行求解并分析其有效前沿.最后，借助数值分析验证了本文所提出模型较现有均值-方差模型的优越性.

Mean-semivariance portfolio optimization model with background risk

In the process of investment decision-making, investors often face not only financial market risks, but also background risks that are independent of the fluctuation of financial asset prices. Most of the existing background risk portfolio models are used variance as risk measure. However, using variance as risk measure has obviously shortcoming. For this, we use semivariance instead of variance as risk measure to investigate a portfolio selection problem with background risk and financial market risks. Then, we propose a mean-semivariance portfolio optimization model with background risk and give a critical line algorithm for solving the proposed model. Meanwhile, we analyze the effective frontier of our model. Finally, we provide a numerical example to make a comparison analysis. The comparative computational results show that the proposed model performs better than the existing mean-variance portfolio model with background risk.