英文标题：
《Key Borrowers Detection by Long-Range Interactions》
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作者：
Fuad Aleskerov, Natalia Meshcheryakova, Alisa Nikitina, Sergey Shvydun
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最新提交年份：
2018
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英文摘要：
We propose a new method for assessing agents\' influence in financial network structures, which takes into consideration the intensity of interactions. A distinctive feature of this approach is that it considers not only direct interactions of agents of the first level and indirect interactions of the second level, but also long-range indirect interactions. At the same time we take into account the attributes of agents as well as the possibility of impact to a single agent from a group of other agents. This approach helps us to identify systemically important elements which cannot be detected by classical centrality measures or other indices. The proposed method was used to analyze the banking foreign claims for the end of 1Q 2015. Under the approach, two types of key borrowers were detected: a) major players with high ratings and positive credit history; b) intermediary players, which have a great scale of financial activities through the organization of favorable investment conditions and positive business climate.
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中文摘要：
我们提出了一种新的方法来评估代理在金融网络结构中的影响，该方法考虑了交互的强度。这种方法的一个显著特点是，它不仅考虑了第一级代理的直接交互和第二级代理的间接交互，还考虑了远程间接交互。同时，我们考虑了代理的属性以及一组其他代理对单个代理的影响的可能性。这种方法有助于我们识别经典的中心性度量或其他指数无法检测到的系统重要元素。所提出的方法用于分析2015年1季度末的银行业外国债权。根据该方法，发现了两类主要借款人：a）具有高评级和良好信用记录的主要借款人；b） 中介机构，通过组织良好的投资条件和积极的商业环境，拥有大规模的金融活动。
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分类信息：

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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