CVAR公司
投资组合优化
文件夹
风险度量
预期短缺
数学优化
光谱风险度量
一致性风险度量
有效边界
偏斜
动态风险度量
风险价值
数学
度量(数据仓库)
最优化问题
计量经济学
计算机科学
经济
风险管理
金融经济学
财务
数据挖掘
作者
Xiang Shi,Young Shin Kim
标识
DOI:10.1142/s0219024921500199
摘要
This paper investigates the coherent risk measure of a class of normal mixture distributions which are widely-used in finance. The main result shows that the mean-risk portfolio optimization problem with these normal mixture distributions can be reduced to a quadratic programming problem which has closed form of solution by fixing the location parameter and skewness parameter. In addition, we show that the efficient frontier of the portfolio optimization problem can be extended to three dimensions in this case. The worst-case value-at-risk in the robust portfolio optimization can also be calculated directly. Finally, the conditional value-at-risk (CVaR) is considered as an example of coherent risk measure. We obtain the marginal contribution to risk for a portfolio based on the normal mixture model.
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