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Constructing financial network based on PMFG and threshold method

机译:基于PMFG和阈值方法构建金融网络

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Based on planar maximally filtered graph (PMFG) and threshold method, we introduced a correlation-based network named PMFG-based threshold network (PTN). We studied the community structure of PTN and applied ISOMAP algorithm to represent PTN in low dimensional Euclidean space. The results show that the community corresponds well to the cluster in the Euclidean space. Further, we studied the dynamics of the community structure and constructed the normalized mutual information (NMI) matrix. Based on the real data in the market, we found that the volatility of the market can lead to dramatic changes in the community structure, and the structure is more stable during the financial crisis. (C) 2017 Elsevier B.V. All rights reserved.
机译:基于平面最大滤波图(PMFG)和阈值方法,我们介绍了一种名为基于PMFG的阈值网络(PTN)的基于相关的网络。 我们研究了PTN的社区结构和应用ISOMAP算法,代表低维欧几里德空间中PTN。 结果表明,社区对欧几里德空间中的集群很好。 此外,我们研究了社区结构的动态,构建了归一化互信息(NMI)矩阵。 基于市场的实际数据,我们发现市场的波动可能导致社区结构的戏剧性变化,在金融危机期间的结构更稳定。 (c)2017年Elsevier B.V.保留所有权利。

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