均值-CVaR模型在资产配置中的应用研究——基于A股市场的分析

The Application of Mean-CVaR Model in Asset Allocation—Analysis Based on A-Share Market

我国股票市场存在着较大的投资风险,探究适用于我国市场风险量化模型,以及将其应用到投资组合优化中具有重大意义。文章研究了均值-CVaR模型在我国A股市场中的应用,利用主成分分析法选择五只不同行业优质股票进行均值-CVaR投资组合优化模型的实证分析。研究结果表明:在风险偏好既定下,随着投资组合预期收益率的提高,最优投资组合中成分股的权重也发生显著变化,资金向平均收益率较高方差较小的股票倾斜,并且投资组合CVaR的值也随之缓慢增大,但始终高于VaR的值。在选定的预期收益率下,随着置信水平的提高CVaR的值也增大,投资者的资金更加集中与少数几个收益率较高的资产。研究结果对A股中不同风险偏好的投资者有较好的风险提示与指导意义。

There is a great investment risk in our stock market, so it is of great significance to study the quantitative model of market risk and apply it to portfolio optimization. This paper studies the application of the mean-CVaR model in our A-share market, and uses principal component anal-ysis to select five high-quality stocks in different industries for the empirical analysis of the mean-CVaR portfolio optimization model. The results show that under the given risk preference, the weight of component stocks in the optimal portfolio changes significantly with the increase of expected return, funds lean toward stocks with higher average returns and smaller variance, and the CVaR of the portfolio slowly increases, but is always higher than the VaR. At the selected expected rate of return, as the confidence level increases the CVaR also increases, investors’ funds are more concentrated with a few higher-yielding assets. The results of this study have a good significance for investors with different risk preference in A-share market.