Identifying the systemic importance and systemic vulnerability of financial institutions based on portfolio similarity correlation network

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS EPJ Data Science Pub Date : 2024-01-31 DOI:10.1140/epjds/s13688-024-00449-2
Manjin Shao, Hong Fan
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Abstract

The indirect correlation among financial institutions, stemming from similarities in their portfolios, is a primary driver of systemic risk. However, most existing research overlooks the influence of portfolio similarity among various types of financial institutions on this risk. Therefore, we construct the network of portfolio similarity correlations among different types of financial institutions, based on measurements of portfolio similarity. Utilizing the expanded fire sale contagion model, we offer a comprehensive assessment of systemic risk for Chinese financial institutions. Initially, we introduce indicators for systemic risk, systemic importance, and systemic vulnerability. Subsequently, we examine the cross-sectional and time-series characteristics of these institutions’ systemic importance and vulnerability within the context of the portfolio similarity correlation network. Our empirical findings reveal a high degree of portfolio similarity between banks and insurance companies, contrasted with lower similarity between banks and securities firms. Moreover, when considering the portfolio similarity correlation network, both the systemic importance and vulnerability of Chinese banks and insurance companies surpass those of securities firms in both cross-sectional and temporal dimensions. Notably, our analysis further illustrates that a financial institution’s systemic importance and vulnerability are strongly and positively associated with the magnitude of portfolio similarity between that institution and others.

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基于投资组合相似性相关网络识别金融机构的系统重要性和系统脆弱性
金融机构之间的间接相关性源于其投资组合的相似性,是系统性风险的主要驱动因素。然而,现有研究大多忽视了各类金融机构之间投资组合相似性对这一风险的影响。因此,我们根据投资组合相似性的测量结果,构建了不同类型金融机构之间的投资组合相似性相关网络。利用扩展的火灾销售传染模型,我们对中国金融机构的系统性风险进行了全面评估。首先,我们介绍了系统性风险、系统重要性和系统脆弱性指标。随后,我们考察了这些机构在投资组合相似性相关网络背景下的系统重要性和脆弱性的横截面和时序特征。我们的实证研究结果表明,银行与保险公司之间的投资组合相似度较高,而银行与证券公司之间的相似度较低。此外,在考虑投资组合相似性相关网络时,中国银行和保险公司的系统重要性和脆弱性在横截面和时间维度上都超过了证券公司。值得注意的是,我们的分析进一步说明,金融机构的系统重要性和脆弱性与该机构与其他机构之间的投资组合相似性大小密切正相关。
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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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