《Capital adequacy tests and limited liability of financial institutions》
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作者:
Pablo Koch-Medina, Santiago Moreno-Bromberg, Cosimo Munari
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最新提交年份:
2014
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英文摘要:
The theory of acceptance sets and their associated risk measures plays a key role in the design of capital adequacy tests. The objective of this paper is to investigate, in the context of bounded financial positions, the class of surplus-invariant acceptance sets. These are characterized by the fact that acceptability does not depend on the positive part, or surplus, of a capital position. We argue that surplus invariance is a reasonable requirement from a regulatory perspective, because it focuses on the interests of liability holders of a financial institution. We provide a dual characterization of surplus-invariant, convex acceptance sets, and show that the combination of surplus invariance and coherence leads to a narrow range of capital adequacy tests, essentially limited to scenario-based tests. Finally, we emphasize the advantages of dealing with surplus-invariant acceptance sets as the primary object rather than directly with risk measures, such as loss-based and excess-invariant risk measures, which have been recently studied by Cont, Deguest, and He (2013) and by Staum (2013), respectively.
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中文摘要:
接受集理论及其相关风险度量在资本充足率测试的设计中起着关键作用。本文的目的是研究在有限财务状况下,剩余不变接受集的类别。其特点是,可接受性并不取决于资本头寸的积极部分或盈余。我们认为,从监管角度来看,盈余不变性是一个合理的要求,因为它关注的是金融机构负债持有人的利益。我们提供了盈余不变性、凸接受集的双重特征,并表明盈余不变性和一致性的结合导致资本充足率测试的范围很窄,基本上仅限于基于情景的测试。最后,我们强调了将剩余不变接受集作为主要对象处理的优势,而不是直接处理风险度量,例如基于损失的风险度量和剩余不变风险度量,最近Cont、Deguest和He(2013)以及Staum(2013)分别对此进行了研究。
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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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