英文标题：
《Risk-dependent centrality in economic and financial networks》
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作者：
Paolo Bartesaghi, Michele Benzi, Gian Paolo Clemente, Rosanna Grassi
and Ernesto Estrada
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最新提交年份：
2020
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英文摘要：
Node centrality is one of the most important and widely used concepts in the study of complex networks. Here, we extend the paradigm of node centrality in financial and economic networks to consider the changes of node \"importance\" produced not only by the variation of the topology of the system but also as a consequence of the external levels of risk to which the network as a whole is submitted. Starting from the \"Susceptible-Infected\" (SI) model of epidemics and its relation to the communicability functions of networks we develop a series of risk-dependent centralities for nodes in (financial and economic) networks. We analyze here some of the most important mathematical properties of these risk-dependent centrality measures. In particular, we study the newly observed phenomenon of ranking interlacement, by means of which two entities may interlace their ranking positions in terms of risk in the network as a consequence of the change in the external conditions only, i.e., without any change in the topology. We test the risk-dependent centralities by studying two real-world systems: the network generated by collecting assets of the S\\&P 100 and the corporate board network of the US top companies, according to Forbes in 1999. We found that a high position in the ranking of the analyzed financial companies according to their risk-dependent centrality corresponds to companies more sensitive to the external market variations during the periods of crisis.
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中文摘要：
节点中心性是复杂网络研究中最重要、应用最广泛的概念之一。在这里，我们扩展了金融和经济网络中节点中心性的范式，以考虑节点“重要性”的变化，这种变化不仅是由系统拓扑结构的变化引起的，而且也是由于整个网络所面临的外部风险水平的结果。从流行病的“易感感染”（SI）模型及其与网络传播功能的关系出发，我们为（金融和经济）网络中的节点开发了一系列风险依赖中心。我们在此分析这些风险相关中心度度量的一些最重要的数学特性。特别是，我们研究了新观察到的排名交错现象，通过这种现象，两个实体可以仅因外部条件的变化而交错其在网络中的风险排名，即拓扑结构没有任何变化。我们通过研究两个现实世界的系统来测试风险相关的中心性：根据《福布斯》（Forbes）1999年的数据，这两个系统是通过收集标准普尔100指数的资产生成的网络和美国顶级公司的公司董事会网络。我们发现，在所分析的金融公司中，根据其风险依赖中心度，排名较高的公司对应于在危机期间对外部市场变化更敏感的公司。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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