摘要翻译：
针对风险资产组合中基于方差-协方差的风险分配问题，提出了一种高精度的解析逼近方法。考虑了具有随机恢复的单周期多因子Merton型模型的一般情形。与Monte Carlo模拟进行了比较，结果表明该方法的精度和速度都优于Monte Carlo模拟。
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英文标题：
《Variance-covariance based risk allocation in credit portfolios:
  analytical approximation》
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作者：
Mikhail Voropaev
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最新提交年份：
2009
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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一级分类：Quantitative Finance        数量金融学
二级分类：Computational Finance        计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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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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英文摘要：
  High precision analytical approximation is proposed for variance-covariance based risk allocation in a portfolio of risky assets. A general case of a single-period multi-factor Merton-type model with stochastic recovery is considered. The accuracy of the approximation as well as its speed are compared to and shown to be superior to those of Monte Carlo simulation.
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PDF链接：
https://arxiv.org/pdf/0905.0781