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摘要翻译：
我们探讨了重要性抽样在结构化信用衍生品(CDO)的蒙特卡罗定价中的可能性。CDO合约的建模具有挑战性，因为它依赖于一个（通常约100）资产池，蒙特卡罗模拟通常是唯一可行的定价方法。方差减少技术因此是非常重要的。本文利用Laplace变换和MC重要抽样结果，对一种易于处理的基于强度的CDO模型，即复合泊松模型，给出了精确的解析解。并导出了再加重效率的解析公式。计算增益是很有吸引力的，然而，即使在这个基本方案中，也可以发现一个相变，使一些参数状态变得遥不可及。本文还提出了一种模型无关的CDO定价方法。
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英文标题：
《Analytic results and weighted Monte Carlo simulations for CDO pricing》
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作者：
Marcell Stippinger and B\'alint Vet\H{o} and \'Eva R\'acz and Zsolt
Bihary
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最新提交年份：
2011
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分类信息：
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：
We explore the possibilities of importance sampling in the Monte Carlo pricing of a structured credit derivative referred to as Collateralized Debt Obligation (CDO). Modeling a CDO contract is challenging, since it depends on a pool of (typically about 100) assets, Monte Carlo simulations are often the only feasible approach to pricing. Variance reduction techniques are therefore of great importance. This paper presents an exact analytic solution using Laplace-transform and MC importance sampling results for an easily tractable intensity-based model of the CDO, namely the compound Poissonian. Furthermore analytic formulae are derived for the reweighting efficiency. The computational gain is appealing, nevertheless, even in this basic scheme, a phase transition can be found, rendering some parameter regimes out of reach. A model-independent transform approach is also presented for CDO pricing.
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PDF链接：
https://arxiv.org/pdf/1105.5416
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