摘要翻译：
在多名称信贷建模的自上而下方法中，至少在原则上，在所谓的随机细化(RT)程序中，计算单个名称的敏感性似乎是可能的，该程序将投资组合风险分解为单个贡献。我们试图构建一个实用的RT框架，该框架能够在自顶向下的框架中高效地计算单个名称的敏感性，并可以扩展到定制部分的估值和风险管理。此外，我们提出了一个动态扩展的RT方法，使建模的特点和违约条件下的个人利差动态在蒙特卡罗设置，以一种方式保持投资组合的“顶级”动态。这就产生了一个模型，它不仅被校准为分段和单个名称的利差，而且还可以被调整为近似匹配给定的利差挥发水平和投资组合中名称的相关性。
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英文标题：
《Climbing Down from the Top: Single Name Dynamics in Credit Top Down
  Models》
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作者：
Igor Halperin and Pascal Tomecek
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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：Pricing of Securities        证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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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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英文摘要：
  In the top-down approach to multi-name credit modeling, calculation of singe name sensitivities appears possible, at least in principle, within the so-called random thinning (RT) procedure which dissects the portfolio risk into individual contributions. We make an attempt to construct a practical RT framework that enables efficient calculation of single name sensitivities in a top-down framework, and can be extended to valuation and risk management of bespoke tranches. Furthermore, we propose a dynamic extension of the RT method that enables modeling of both idiosyncratic and default-contingent individual spread dynamics within a Monte Carlo setting in a way that preserves the portfolio "top"-level dynamics. This results in a model that is not only calibrated to tranche and single name spreads, but can also be tuned to approximately match given levels of spread volatilities and correlations of names in the portfolio.
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PDF链接：
https://arxiv.org/pdf/0901.3404