日本的银行公司信贷网络。二部网络的分析

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英文标题：
《Bank-firm credit network in Japan. An analysis of a bipartite network》
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作者：
Luca Marotta, Salvatore Miccich\\`e, Yoshi Fujiwara, Hiroshi Iyetomi,
  Hideaki Aoyama, Mauro Gallegati, Rosario N. Mantegna
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最新提交年份：
2014
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英文摘要：
  We present an analysis of the credit market of Japan. The analysis is performed by investigating the bipartite network of banks and firms which is obtained by setting a link between a bank and a firm when a credit relationship is present in a given time window. In our investigation we focus on a community detection algorithm which is identifying communities composed by both banks and firms. We show that the clusters obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. Specifically, we obtain communities of banks and networks for each of the 32 investigated years, and we introduce a method to track the time evolution of these communities on a statistical basis. We then characterize communities by detecting the simultaneous over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32 year long analysis we detect a persistence of the over-expression of attributes of clusters of banks and firms together with a slow dynamics of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks and economic sector of the firm play a role in shaping the credit relationships between banks and firms.
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中文摘要：
我们对日本的信贷市场进行了分析。分析是通过调查银行和企业的二分网络来进行的，这是在给定的时间窗口内存在信用关系时，通过设置银行和企业之间的联系而获得的。在我们的调查中，我们重点研究了一种社区检测算法，该算法可以识别由银行和企业组成的社区。我们表明，通过直接在二部网络上工作获得的集群携带有关日本信贷市场网络化性质的信息。我们对1980年至2011年期间的每个日历年进行分析。具体来说，我们获得了32年调查中每一年的银行和网络社区，并介绍了一种方法，以统计为基础跟踪这些社区的时间演变。然后，我们通过检测企业和银行属性的同时过度表达来刻画社区。具体而言，我们将经济部门、公司地理位置和银行类型视为属性。在我们长达32年的分析中，我们发现银行和企业集群的属性持续过度表达，以及从某些特定属性到新属性的缓慢变化。我们的实证观察表明，日本的信贷市场是一个网络化的市场，银行类型、企业和银行的地理位置以及企业的经济部门在塑造银行和企业之间的信贷关系方面发挥着作用。
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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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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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关键词：公司信贷 Quantitative relationship Geographical observations