评级系统中违约风险与模型不确定性的公理化方法
An axiomatic approach to default risk and model uncertainty in rating systems
AI总结：
本文提出违约风险度量的公理化框架，推广经典违约概率以纳入模型风险，并分析最坏情况PD与扭曲PD对风险加权资产计算的影响。
摘要：
本文研究违约风险的公理化方法。我们引入违约风险度量的概念，它推广了经典的违约概率（PD），并允许以多种形式纳入模型风险。我们讨论了违约风险度量通过货币风险度量、相关尾部风险度量族以及Choquet容度的不同性质与表示。第二步，我们将关注点转向以最坏情况PD和扭曲PD形式给出的违约风险度量。后者经常被用于在计算资本要求时考虑模型风险，具体通过风险加权资产（RWAs）实现，这是资本要求条例（CRR）所要求的。在这一背景下，我们讨论了不同违约风险度量和保守性边际对风险加权资产数量的影响。
英文摘要：
In this paper, we deal with an axiomatic approach to default risk. We introduce the notion of a default risk measure, which generalizes the classical probability of default (PD), and allows to incorporate model risk in various forms. We discuss different properties and representations of default risk measures via monetary risk measures, families of related tail risk measures, and Choquet capacities. In a second step, we turn our focus on default risk measures, which are given as worst-case PDs and distorted PDs. The latter are frequently used in order to take into account model risk for the computation of capital requirements through risk-weighted assets (RWAs), as demanded by the Capital Requirement Regulation (CRR). In this context, we discuss the impact of different default risk measures and margins of conservatism on the amount of risk-weighted assets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
