| 刘遵雄,盛亚雄.权重分离性约束的Mean-CVaR投资组合模型[J].井冈山大学自然版,2017,(3):19-24,29 |
| 权重分离性约束的Mean-CVaR投资组合模型 |
| MEAN-CVAR PORTFOLIO MODEL WITH WEIGHT SEPARATION CONSTRAINTS |
| 投稿时间：2016-07-01 修订日期：2016-10-16 |
| DOI：10.3969/j.issn.1674-8085.2017.03.004 |
| 中文关键词: Conditional Value at Risk 投资组合 Mean-CVaR |
| 英文关键词: Conditional Value at Risk portfolio Mean-CVaR |
| 基金项目:国家自然科学基金项目（71361009） |
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| 摘要点击次数: 1798 |
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| 中文摘要: |
| 不同于均值-方差（Mean-Variance）模型，均值-条件风险价值（Mean-Conditional Value at Risk，Mean-CVaR）模型不是以投资组合收益的方差作为风险测度，而是使用了能表征投资收益下侧尾部风险的条件风险价值。同样，Mean-CVaR模型存在优化解微权值数目过多的问题，造成操作性下降。针对这些问题，提出了在Mean-CVaR模型引入权值分离性约束，以保证投资权值不低于某一设定的阈值，结合上证50指数股票进行实例分析。 |
| 英文摘要: |
| Different from the Mean-Variance, the Mean-CVaR (Mean-Conditional value at risk) model didn't take the variance of the portfolio returns as a measure of risk. However, it uses the conditional value at risk that express the underside of the tail risk of the investment income. Similarly, the optimal solution of Mean-CVaR problem has a lot of micro weight, which results in the decline of operating. The constraint of weight separation is proposed in this paper into the mean-CVaR model, which can ensures that the value of investment weight is not less than a set threshold. Combined with the SSE 50 index stock, we carry on the example analysis. |
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