摘要翻译：
近年来，信用风险模型的研究主要集中在违约概率方面。回收率通常是独立建模的，通常甚至假设它们是恒定的。然而，这样，回收率和违约概率之间的结构联系就失去了，损失分布的尾部可能被大大低估。当考虑到校准问题时，低估尾部损失的问题变得更加严重。为了证明这一点，我们选择了默顿型结构模型作为我们的参考系。扩散和跳跃扩散被认为是潜在的过程。我们对该模型进行了蒙特卡罗模拟，并根据模拟数据校准了不同的恢复模型。为了简单起见，我们直接从模拟数据中获取默认概率。我们比较了约化形式的恢复模型和常数恢复方法。另外，我们考虑了恢复率和违约概率之间的函数依赖关系。对于扩散情形，这种依赖关系可以解析地导出。我们发现，常数恢复方法急剧和系统地低估了损失分布的尾部。当所有模拟数据都用于校准时，简化形式恢复模型显示出更好的结果。然而，如果我们限制用于校准的模拟数据，简化模型的结果会恶化。当我们利用恢复率和违约概率之间的函数依赖关系时，我们找到了最可靠和最稳定的结果。
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英文标题：
《Calibration of structural and reduced-form recovery models》
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作者：
Alexander F. R. Koivusalo and Rudi Sch\"afer
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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：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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英文摘要：
  In recent years research on credit risk modelling has mainly focused on default probabilities. Recovery rates are usually modelled independently, quite often they are even assumed constant. Then, however, the structural connection between recovery rates and default probabilities is lost and the tails of the loss distribution can be underestimated considerably. The problem of underestimating tail losses becomes even more severe, when calibration issues are taken into account. To demonstrate this we choose a Merton-type structural model as our reference system. Diffusion and jump-diffusion are considered as underlying processes. We run Monte Carlo simulations of this model and calibrate different recovery models to the simulation data. For simplicity, we take the default probabilities directly from the simulation data. We compare a reduced-form model for recoveries with a constant recovery approach. In addition, we consider a functional dependence between recovery rates and default probabilities. This dependence can be derived analytically for the diffusion case. We find that the constant recovery approach drastically and systematically underestimates the tail of the loss distribution. The reduced-form recovery model shows better results, when all simulation data is used for calibration. However, if we restrict the simulation data used for calibration, the results for the reduced-form model deteriorate. We find the most reliable and stable results, when we make use of the functional dependence between recovery rates and default probabilities.
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PDF链接：
https://arxiv.org/pdf/1102.4864