英文标题：
《A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios》
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作者：
Th\\\'eophile Griveau-Billion, Jean-Charles Richard and Thierry Roncalli
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最新提交年份：
2013
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英文摘要：
In this paper we propose a cyclical coordinate descent (CCD) algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast even with large covariance matrices (n > 500). Comparison with existing algorithms also shows that it is one of the most efficient algorithms.
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中文摘要：
本文提出了一种求解高维风险奇偶性问题的循环坐标下降（CCD）算法。我们证明了该算法的收敛性，并且即使在协方差矩阵较大（n>500）的情况下也非常快。与现有算法的比较也表明它是最有效的算法之一。
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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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