基于条件风险价值的投资组合优化模型

采用R T Rockafellar和S Uryasev的一种优化算法，构造了一个以条件风险价值代替标准差度量风险的投资组合优化模型．选择沪、深股市6种股票构成一个投资组合，用Matlab软体对模型进行优化计算，得到了该投资组合的有效前沿和投资权重，并与用传统的均值方差模型的计算结果进行了比较．结果表明，这2个模型优化得到的有效前沿非常相近，与国外研究获得的有效前沿图形也非常相似，但这2个模型优化得到的投资权重却有较大差异．

Portfolio Optimization Model Based on Conditional Value-at-Risk

Based on an algorithm proposed by R T Rockafeller and S Uryasev, a portfolio optimization model, mean-conditional value-at-risk model, was set up. This model measures risk with conditional value-at-risk (CVaR) instead of standard deviation. It was optimized by using Matlab software and choosing six stocks in Shanghai and Shenzhen stock markets in China as a portfolio, and efficient frontier and investment proportion of the portfolio were obtained. By comparing them with the ones obtained using the traditional mean-variance (MV) model, the result indicates that the efficient frontiers gained by the two models are almost identical and also close to overseas research results, but there is a difference between the optimal investment proportions based on the mean-CVaR model and the MV model.