英文标题：
《Mesoscopic Community Structure of Financial Markets Revealed by Price
  and Sign Fluctuations》
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作者：
Assaf Almog, Ferry Besamusca, Mel MacMahon, Diego Garlaschelli
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最新提交年份：
2015
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英文摘要：
  The mesoscopic organization of complex systems, from financial markets to the brain, is an intermediate between the microscopic dynamics of individual units (stocks or neurons, in the mentioned cases), and the macroscopic dynamics of the system as a whole. The organization is determined by \"communities\" of units whose dynamics, represented by time series of activity, is more strongly correlated internally than with the rest of the system. Recent studies have shown that the binary projections of various financial and neural time series exhibit nontrivial dynamical features that resemble those of the original data. This implies that a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. Here, we explore whether the binary signatures of multiple time series can replicate the same complex community organization of the financial market, as the original weighted time series. We adopt a method that has been specifically designed to detect communities from cross-correlation matrices of time series data. Our analysis shows that the simpler binary representation leads to a community structure that is almost identical with that obtained using the full weighted representation. These results confirm that binary projections of financial time series contain significant structural information.
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中文摘要：
从金融市场到大脑的复杂系统的介观组织，是单个单元（在上述情况下为股票或神经元）的微观动力学与整个系统的宏观动力学之间的中间环节。组织由单位的“社区”决定，其动态（由活动的时间序列表示）在内部比与系统其他部分的相关性更强。最近的研究表明，各种金融和神经时间序列的二元预测显示出与原始数据相似的非平凡动力学特征。这意味着一条重要的信息被编码到这种增量的二进制投影（即符号）中。在这里，我们探讨了多个时间序列的二进制签名是否可以复制金融市场的同一复杂社区组织，就像原始加权时间序列一样。我们采用了一种专门设计的方法，从时间序列数据的互相关矩阵中检测社区。我们的分析表明，更简单的二进制表示会产生一个社区结构，该结构与使用全加权表示得到的社区结构几乎相同。这些结果证实，金融时间序列的二元预测包含重要的结构信息。
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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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一级分类：Physics        物理学
二级分类：Data Analysis, Statistics and Probability        数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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