如何衡量银行、保险公司和金融集团之间的相互联系

IF 1.3 Q2 STATISTICS & PROBABILITY
Hauton Gaël, Héam Jean-Cyprien
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引用次数: 8

摘要

金融机构的相互关联性是系统性风险的关键组成部分。然而,对其测量方法仍未达成共识。利用法国金融机构风险敞口网络的独特数据库,我们比较了三种衡量互联性的策略:风险敞口分布的紧密性、核心-外围结构的识别和传染模型。暴露分布的密切性足以识别离群机构。通常适用于银行网络的“核心-外围”结构对保险公司仍然有效。然而,这种方法并非不受规模效应的影响。这一结果与之前没有考虑大小的分析形成对比。基于传染的压力测试最适合捕捉机构的系统性脆弱性,强调它们作为监管工具的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to measure interconnectedness between banks, insurers and financial conglomerates
Financial institutions’ interconnectedness is a key component of systemic risk. However there is still no consensus on its measurement. Using a unique database of network of exposures of French financial institutions, we compare three strategies to measure interconnectedness: closeness of exposure distributions, identification of core-periphery structure and contagion models. The closeness of exposure distributions is adequate to identify outlier institutions. The “core-periphery” structure, usually applied to banking network, is still valid with insurance companies. However this approach is not immune to size effect. This result contrasts with previous analyses where size was not accounted for. Contagion-based stress-tests are the best suited to capture institutions’ systemic fragility, emphasizing their importance as a supervisory tool.
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来源期刊
Statistics & Risk Modeling
Statistics & Risk Modeling STATISTICS & PROBABILITY-
CiteScore
1.80
自引率
6.70%
发文量
6
期刊介绍: Statistics & Risk Modeling (STRM) aims at covering modern methods of statistics and probabilistic modeling, and their applications to risk management in finance, insurance and related areas. The journal also welcomes articles related to nonparametric statistical methods and stochastic processes. Papers on innovative applications of statistical modeling and inference in risk management are also encouraged. Topics Statistical analysis for models in finance and insurance Credit-, market- and operational risk models Models for systemic risk Risk management Nonparametric statistical inference Statistical analysis of stochastic processes Stochastics in finance and insurance Decision making under uncertainty.
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