详细信息
Structural properties of statistically validated empirical information networks ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Structural properties of statistically validated empirical information networks
作者:Han, Rui-Qi[1,2,3,4];Li, Ming-Xia[2,5];Chen, Wei[6];Zhou, Wei-Xing[1,2,7];Stanley, H. Eugene[3,4]
机构:[1]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[3]Boston Univ, Dept Phys, Boston, MA 02215 USA;[4]Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USA;[5]East China Univ Sci & Technol, Res Inst Sports Econ, Shanghai 200237, Peoples R China;[6]Shenzhen Stock Exchange, Shenzhen 518010, Peoples R China;[7]East China Univ Sci & Technol, Dept Finance, Shanghai 200237, Peoples R China
年份:2019
卷号:523
起止页码:747
外文期刊名:PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
收录:;EI(收录号:20191106631821);WOS:【SSCI(收录号:WOS:000470954500065),SCI-EXPANDED(收录号:WOS:000470954500065)】;
基金:This work was partly supported by the National Natural Science Foundation of China (71571121, 71532009, U1811462) and the Fundamental Research Funds for the Central Universities, China (222201818006).
语种:英文
外文关键词:Econophysics; Empirical information network; Statistically validated networks; Mixing patterns; Trading behavior
摘要:We construct the empirical information network (EIN) of traders using the order flow data of the constituent stocks of SZSE 100 Index in 2013. A statistical validation method is applied to the edges of the network to filter out noises and uncover the intrinsic interaction behaviors of traders. We investigate the correlation between topological structures and statistical properties for their largest connected components. We find that the statistical validated network shows an assortative mixing pattern while the original network exhibits a disassortative mixing pattern. We consider two definitions of edge weight for comparison but there is no significant difference in a same network. We also analyze the mutual relationships among node degree, edge weight and node strength. (C) 2019 Elsevier B.V. All rights reserved.
参考文献:
正在载入数据...
