摘要翻译：
我们运用网络科学的方法研究1991-2008年间外汇市场的相关性。我们考虑一个外汇市场网络，其中每个节点代表一个汇率，每个加权边代表汇率之间的时间相关。为了深入研究汇率时间序列的聚类，我们研究了网络中的动态社区。我们证明了汇率在市场中的功能角色与其在共同体中的地位之间存在关系，并使用以节点为中心的共同体分析来跟踪这种角色的时间动态。这揭示了哪些汇率在特定时期主导市场，也确定了市场作用经历重大变化的汇率。我们还利用社区动态来揭示发生在外汇市场的主要结构性变化。我们的技术是通用的，对于调查其他市场的相关性同样有用。
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英文标题：
《Dynamical Clustering of Exchange Rates》
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作者：
Daniel J. Fenn, Mason A. Porter, Peter J. Mucha, Mark McDonald, Stacy
  Williams, Neil F. Johnson, Nick S. Jones
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最新提交年份：
2010
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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一级分类：Physics        物理学
二级分类：Adaptation and Self-Organizing Systems        自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
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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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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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英文摘要：
  We use techniques from network science to study correlations in the foreign exchange (FX) market over the period 1991--2008. We consider an FX market network in which each node represents an exchange rate and each weighted edge represents a time-dependent correlation between the rates. To provide insights into the clustering of the exchange rate time series, we investigate dynamic communities in the network. We show that there is a relationship between an exchange rate's functional role within the market and its position within its community and use a node-centric community analysis to track the time dynamics of this role. This reveals which exchange rates dominate the market at particular times and also identifies exchange rates that experienced significant changes in market role. We also use the community dynamics to uncover major structural changes that occurred in the FX market. Our techniques are general and will be similarly useful for investigating correlations in other markets.
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PDF链接：
https://arxiv.org/pdf/0905.4912