Topological structures in the equities market network
Topological structures in the equities market network
复制标题
DOI：
10.1073/pnas.0802806106
复制
发表时间：
2008-12-30
影响因子：
11.1
通讯作者：
Savell, Robert
中科院分区：
文献类型：
--
作者：
Leibon, Gregory;Pauls, Scott;Savell, Robert
我们提出了一种新方法，用于阐明许多复杂系统中固有的网络结构的尺度相关拓扑描述。该技术基于“分区解耦零模型”，这是一类新的零模型，它将集群分区的相互作用纳入随机模型并推广高斯系综。作为一种应用，我们分析了从纽约证券交易所 (NYSE) 和全国证券交易商自动报价协会 (NASDAQ) 股票 4 年收盘价得出的相关矩阵。在这个示例中，我们公开了 (i) 由 2 个相互作用的分区组成的自然结构。市场既同意并概括了规模的标准概念（例如，部门和行业），并且（ii）第一个分区中的结构是众所周知的资本流动模式（称为“部门轮换”）的拓扑表现。我们的方法产生了对基础时间序列进行多分辨率分析的自然形式，该分析自然地根据其聚类的不同规模的影响来分解基本数据。我们通过对具有嵌入式拓扑结构的模拟网络的成功分析来支持我们的结论，并展示了该技术的稳健性。股票市场是一个典型的复杂系统，我们期望我们的方法将有助于理解存在相关结构的一类广泛的复杂系统。
We present a new method for articulating scale-dependent topological descriptions of the network structure inherent in many complex systems. The technique is based on "partition decoupled null models,'' a new class of null models that incorporate the interaction of clustered partitions into a random model and generalize the Gaussian ensemble. As an application, we analyze a correlation matrix derived from 4 years of close prices of equities in the New York Stock Exchange (NYSE) and National Association of Securities Dealers Automated Quotation (NASDAQ). In this example, we expose (i) a natural structure composed of 2 interacting partitions of the market that both agrees with and generalizes standard notions of scale (e.g., sector and industry) and (ii) structure in the first partition that is a topological manifestation of a well-known pattern of capital flow called "sector rotation.'' Our approach gives rise to a natural form of multiresolution analysis of the underlying time series that naturally decomposes the basic data in terms of the effects of the different scales at which it clusters. We support our conclusions and show the robustness of the technique with a successful analysis on a simulated network with an embedded topological structure. The equities market is a prototypical complex system, and we expect that our approach will be of use in understanding a broad class of complex systems in which correlation structures are resident.