英文标题：
《A review of two decades of correlations, hierarchies, networks and
  clustering in financial markets》
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作者：
Gautier Marti, Frank Nielsen, Miko{\\l}aj Bi\\\'nkowski, Philippe Donnat
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最新提交年份：
2020
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英文摘要：
  We review the state of the art of clustering financial time series and the study of their correlations alongside other interaction networks. The aim of this review is to gather in one place the relevant material from different fields, e.g. machine learning, information geometry, econophysics, statistical physics, econometrics, behavioral finance. We hope it will help researchers to use more effectively this alternative modeling of the financial time series. Decision makers and quantitative researchers may also be able to leverage its insights. Finally, we also hope that this review will form the basis of an open toolbox to study correlations, hierarchies, networks and clustering in financial markets.
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中文摘要：
我们回顾了金融时间序列聚类的最新进展，以及它们与其他交互网络的相关性研究。本综述的目的是在一个地方收集来自不同领域的相关材料，例如机器学习、信息几何、经济物理学、统计物理学、计量经济学、行为金融学。我们希望这将帮助研究人员更有效地使用这种金融时间序列的替代模型。决策者和定量研究人员也可以利用其见解。最后，我们还希望此次审查将形成一个开放工具箱的基础，以研究金融市场中的相关性、层级、网络和集群。
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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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