英文标题：
《Portfolio Selection with Multiple Spectral Risk Constraints》
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作者：
Carlos Abad and Garud Iyengar
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最新提交年份：
2015
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英文摘要：
We propose an iterative gradient-based algorithm to efficiently solve the portfolio selection problem with multiple spectral risk constraints. Since the conditional value at risk (CVaR) is a special case of the spectral risk measure, our algorithm solves portfolio selection problems with multiple CVaR constraints. In each step, the algorithm solves very simple separable convex quadratic programs; hence, we show that the spectral risk constrained portfolio selection problem can be solved using the technology developed for solving mean-variance problems. The algorithm extends to the case where the objective is a weighted sum of the mean return and either a weighted combination or the maximum of a set of spectral risk measures. We report numerical results that show that our proposed algorithm is very efficient; it is at least one order of magnitude faster than the state-of-the-art general purpose solver for all practical instances. One can leverage this efficiency to be robust against model risk by including constraints with respect to several different risk models.
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中文摘要：
我们提出了一种基于迭代梯度的算法来有效地解决多光谱风险约束下的投资组合选择问题。由于条件风险值（CVaR）是谱风险度量的一种特殊情况，我们的算法解决了具有多个CVaR约束的投资组合选择问题。在每一步中，该算法求解非常简单的可分离凸二次规划；因此，我们证明了谱风险约束的投资组合选择问题可以使用为解决均值-方差问题而开发的技术来解决。该算法扩展到目标是平均收益和一组谱风险度量的加权组合或最大值的加权和的情况。我们报告的数值结果表明，我们提出的算法是非常有效的；对于所有实际情况，它至少比最先进的通用解算器快一个数量级。我们可以利用这种效率，通过包含多个不同风险模型的约束，对模型风险具有鲁棒性。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类：Mathematics 数学
二级分类：Optimization and Control 优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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