摘要翻译：
我们研究了在面临信用风险的企业网络中传染的影响。我们描述了一个基于强度的模型，该模型通过引入随机环境打破了同质性假设，使得考虑企业的特殊性成为可能。我们将看到，我们的模型是在识别可以被认为基本上是可交换的公司集团之后。尽管存在这种异构假设，我们的模型仍然具有完全易于处理的优势。其目的是量化一家银行在一个大的信贷组合中可能遭受的损失。基于过程轨迹空间上的大偏差原理，我们给出了一个适用于研究投资组合大损失的大数定律和中心极限定理。给出了仿真结果以及在证券组合损失分布分析中的应用。
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英文标题：
《Heterogeneous credit portfolios and the dynamics of the aggregate losses》
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作者：
Paolo Dai Pra, Marco Tolotti
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最新提交年份：
2008
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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：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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英文摘要：
  We study the impact of contagion in a network of firms facing credit risk. We describe an intensity based model where the homogeneity assumption is broken by introducing a random environment that makes it possible to take into account the idiosyncratic characteristics of the firms. We shall see that our model goes behind the identification of groups of firms that can be considered basically exchangeable. Despite this heterogeneity assumption our model has the advantage of being totally tractable. The aim is to quantify the losses that a bank may suffer in a large credit portfolio. Relying on a large deviation principle on the trajectory space of the process, we state a suitable law of large number and a central limit theorem useful to study large portfolio losses. Simulation results are provided as well as applications to portfolio loss distribution analysis.
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PDF链接：
https://arxiv.org/pdf/0806.3399