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Network, market, and book-based systemic risk rankings

机译:网络,市场和基于书籍的系统风险排名

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摘要

We investigate the information content of stock correlation based network measures for systemic risk rankings, such as SIFIRank (based on Google's PageRank). Using European banking data, we show that SIFIRank is empirically equivalent to a ranking based on average pairwise stock correlations as developed in this paper. The correlation based network measures complement currently available alternative systemic risk ranking methods based on book or market values. A further analytical investigation shows that the value-added appears to be mainly attributable to pairwise cross-sectional heterogeneity rather than to more subtle network relations and feedback loops. (C) 2017 Elsevier B.V. All rights reserved.
机译:我们调查基于股票相关性的网络度量的信息内容,以进行系统性风险排名,例如SIFIRank(基于Google的PageRank)。使用欧洲银行业数据,我们显示出SIFIRank在经验上等效于本文中基于平均成对股票相关性的排名。基于相关性的网络度量补充了基于账面价值或市场价值的当前可用的替代系统性风险排名方法。进一步的分析研究表明,增值似乎主要归因于成对的横截面异质性,而不是更微妙的网络关系和反馈回路。 (C)2017 Elsevier B.V.保留所有权利。

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