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Evaluating systemic risk using bank default probabilities in financial networks

机译:使用金融网络中的银行违约概率评估系统风险

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摘要

In this paper, we propose a novel methodology to measure systemic risk in networks composed of financial institutions. Our procedure combines the impact effects obtained from stress measures that rely on feedback centrality properties with the default probabilities of institutions. We also present new heuristics for designing feasible and relevant stress-testing scenarios that can subside regulators in financial system surveillance tasks. We develop a methodology to extract banking communities and show that these communities have a relevant effect on systemic risk. We find that these communities are mostly composed of non-large banks, suggesting that regulators should also broaden their surveillance efforts to these banking communities other than to the usual SIFIs and large banks. Finally, our results provide insights and guidelines for policymakers. (C) 2016 Elsevier B.V. All rights reserved.
机译:在本文中,我们提出了一种新的方法来衡量由金融机构组成的网络中的系统性风险。我们的过程将依赖于反馈中心性属性的压力测度获得的影响效果与机构的默认概率结合在一起。我们还提出了新的启发式方法,用于设计可行且相关的压力测试方案,这些方案可以使监管机构在金融系统监视任务中得到缓解。我们开发了一种方法来提取银行业社区,并表明这些社区对系统性风险具有相关影响。我们发现这些社区主要由非大型银行组成,这表明监管机构还应将监管工作扩展到这些银行社区,而不是通常的SIFI和大型银行。最后,我们的结果为决策者提供了见识和指导方针。 (C)2016 Elsevier B.V.保留所有权利。

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