多通道数据中的动态社区：2007- 2008年信贷危机期间外汇市场的应用
Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis
摘要：
我们研究集群动态的多通道（多变量）时间序列表示其相关性的时间依赖网络和调查网络社区的演变。我们采用了以节点为中心的方法，使我们能够跟踪社区演变对单个节点的功能角色的影响，而不必跟踪整个社区。作为一个例子，我们考虑一个外汇市场网络，其中每个节点代表一个汇率，每个边代表汇率之间的时间相关性。我们研究了2005-2008年期间，其中包括最近的信贷和流动性危机。使用动态社区检测，我们发现，强烈地附着到他们的社区的汇率持续分组与相同的一组汇率，而汇率是重要的信息传递往往被定位在社区的边缘。我们的分析成功地揭示了信贷危机期间市场发生的重大交易变化。
英文摘要：
We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using dynamical community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
