基于条件风险价值的投资组合优化模型
Portfolio Optimization Model Based on Conditional Value-at-Risk
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摘要: 采用RTRockafellar和SUryasev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.Abstract: 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 riskwith conditional value- at-risk (CVaR) instead of standard deviation. It was optimized by using Matlab software and choosing six stocks in Shanghai and Shenzhen stockmarkets 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 MVmodel.
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