英文标题：
《Dynamic Multi-Factor Clustering of Financial Networks》
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作者：
Gordon J. Ross
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最新提交年份：
2015
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英文摘要：
  We investigate the tendency for financial instruments to form clusters when there are multiple factors influencing the correlation structure. Specifically, we consider a stock portfolio which contains companies from different industrial sectors, located in several different countries. Both sector membership and geography combine to create a complex clustering structure where companies seem to first be divided based on sector, with geographical subclusters emerging within each industrial sector. We argue that standard techniques for detecting overlapping clusters and communities are not able to capture this type of structure, and show how robust regression techniques can instead be used to remove the influence of both sector and geography from the correlation matrix separately. Our analysis reveals that prior to the 2008 financial crisis, companies did not tend to form clusters based on geography. This changed immediately following the crisis, with geography becoming a more important determinant of clustering.
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中文摘要：
我们研究了当存在多种因素影响相关结构时，金融工具形成集群的趋势。具体来说，我们考虑一个股票投资组合，其中包含来自不同工业部门、位于几个不同国家的公司。行业成员资格和地理位置共同构成了一个复杂的集群结构，在这个结构中，公司似乎首先根据行业进行划分，每个行业中都出现了地理子集群。我们认为，用于检测重叠集群和社区的标准技术无法捕捉这种类型的结构，并展示了如何使用稳健回归技术来分别从相关矩阵中去除行业和地理的影响。我们的分析表明，在2008年金融危机之前，公司并不倾向于根据地理位置形成集群。这一点在危机之后立即发生了变化，地理位置成为了集群的一个更重要的决定因素。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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