文献类型：期刊文献

英文题名：Analyzing the stock market based on the structure of kNN network

作者：Nie, Chun-Xiao[1];Song, Fu-Tie[1]

机构：[1]East China Univ Sci & Technol, Sch Business, Dept Finance, Shanghai 200237, Peoples R China

年份：2018

卷号：113

起止页码：148

外文期刊名：CHAOS SOLITONS & FRACTALS

收录：;EI(收录号：20182505343454);WOS:【SCI-EXPANDED(收录号:WOS:000442101600018)】；

基金：This research was partially supported by the National Natural Science Foundation of China (Fund Number: 71371073) and Shanghai Pujiang Program of China (Fund Number: 13PJC025).

语种：英文

外文关键词：k nearest neighbors graph; Financial market; Cluster; Random matrix theory

摘要：This paper systematically studies the structure of the financial kNN (k-nearest neighbor) network. First, we use the eigenvalues and eigenvectors of the financial correlation matrix to analyze the structure of the network. We find that the degree is related to the average correlation coefficient, and furthermore, it also has a relationship between the components of the eigenvector corresponding to the maximum eigenvalue. We apply existing research to confirm that the community structure of the kNN network can be used to cluster financial time series. Finally, empirical studies based on financial markets in three countries show that there is a high correlation between the community structure and dimensions. Therefore, this study shows that the structure of the financial kNN network is related to the properties of the correlation matrix, and it extracts a meaningful correlation structure. (C) 2018 Elsevier Ltd. All rights reserved.