英文标题：
《Model Risk in Credit Risk》
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作者：
Roberto Fontana, Elisa Luciano, Patrizia Semeraro
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最新提交年份：
2019
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英文摘要：
The issue of model risk in default modeling has been known since inception of the Academic literature in the field. However, a rigorous treatment requires a description of all the possible models, and a measure of the distance between a single model and the alternatives, consistent with the applications. This is the purpose of the current paper. We first analytically describe all possible joint models for default, in the class of finite sequences of exchangeable Bernoulli random variables. We then measure how the model risk of choosing or calibrating one of them affects the portfolio loss from default, using two popular and economically sensible metrics, Value-at-Risk (VaR) and Expected Shortfall (ES).
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中文摘要：
违约建模中的模型风险问题自该领域的学术文献问世以来就为人所知。然而，严格的处理要求描述所有可能的模型，并测量单个模型与备选方案之间的距离，与应用一致。这就是本文的目的。我们首先在可交换伯努利随机变量的有限序列类中分析描述所有可能的违约联合模型。然后，我们使用两个流行且经济上合理的指标，即风险价值（VaR）和预期缺口（ES），来衡量选择或校准其中一个的模型风险如何影响违约造成的投资组合损失。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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