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A model-based index for systemic risk contribution measurement in financial networks

机译:基于模型的金融网络中的系统风险贡献测量索引

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摘要

Measurement of the potential risk of an institution?s failure to other institutions is essential in detecting vulnerable institutions. Based on the famous model proposed by Eisenberg and Noe (2001), we introduce a novel model-based systemic risk contribution index to quantify the marginal negative externality from the default institution to other institutions. The proposed index clearly distinguishes the contributions of direct and indirect risk transmitted through immediate liability connections and mediate liability chains, respectively. More importantly, it can identify susceptible institutions conditional on a default, which is critical for regulators to take targeted steps to break the chains of risk contagion. As an illustration, we analyze the systemic risk contribution between country pairs using a dataset of 18 Eurozone countries during the European Sovereign Debt Crisis. We find that direct risk contagion dominates in general, but indirect risk contagion still plays a nonnegligible role.
机译:测量机构潜在风险的风险对其他机构的潜在风险对于检测弱势机构来说至关重要。基于Eisenberg和Noe(2001)提出的着名模型,我们介绍了一种基于模型的基于模型的系统风险贡献指数,从而量化默认机构到其他机构的边际负外部性。拟议的指数显然区分了通过立即责任联系和调解责任链传播的直接和间接风险的贡献。更重要的是,它可以识别默认情况下的易感机构,这对于监管机构来说至关重要,以便采取有针对性的步骤来破坏风险传染链。作为一名插图,我们在欧洲主权债务危机期间使用18个欧元区国家的数据集分析国家对之间的全身风险贡献。我们发现,直接风险传染总体占主导地位,但间接风险传染仍然扮演非资格的作用。

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