复杂网络在股票市场相关分析中的应用
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- 英文论文题名：Application of the Complex Network in Stock Market Board Analysis
- 论文作者：肖琴
- 英文论文作者：XIAO Qin ; College of Sciences ; Shanghai Institute of Technology
- 年：2016
- 作者机构：上海应用技术大学理学院;
- 论文关键词：复杂网络 ; 相关距离矩阵 ; 介数 ; 社区结构
- 英文论文关键词：complex network ; correlation metric ; betweenness ; community
- 会议召开时间：2016-11-12
- 会议录名称：第十八届中国管理科学学术年会论文集
- 英文会议录名称：Proceedings of the 18th Chinese Annual Conference on Management Science
- 语种：中文
- 分类号：F224;F832.51
- 学会代码：ZHYJ
- 会议名称：第十八届中国管理科学学术年会
- 会议地点：中国陕西西安
- 主办单位：中国优选法统筹法与经济数学研究会、西安交通大学、中国科学院科技战略咨询研究院、《中国管理科学》编辑部
- 学会名称：中国优选法统筹法与经济数学研究会
- 页数：5
- 文件大小：818k
- 原文格式：O
- 会议级别：全国
摘要
把复杂网络方法应用于股票市场的研究。对中国股票五大类的134个股票数据进行了相关分析,并用相关关系的欧几里德距离建立了描述股票相似性的复杂网络,运用度、紧密度、介数、社区结构等拓扑概念讨论网络的非平凡的结构。把网络分成8个社区,通过对这8个社区的分析表明,复杂网络是股市相关分析中的一种比较有意义的方法,对于投资者选择股票投资提供一定的参考作用。
The complex network has been applied in study of stock market.Properties such as degree,betweenness,closeness,and community are employed to detect nontrivial characteristics in the correlation distance spanning tree and the stock relation network.It is found that the correlation network can be divided into eight communities.It is point that the complex network is an effective way in stock market analysis.
The complex network has been applied in study of stock market.Properties such as degree,betweenness,closeness,and community are employed to detect nontrivial characteristics in the correlation distance spanning tree and the stock relation network.It is found that the correlation network can be divided into eight communities.It is point that the complex network is an effective way in stock market analysis.
引文
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[3]张辆芬.中国股票市场板块轮动的机理分析[J].经济管理与科学决策.2010,(4):139-141.
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[12]Li P,Wang B H.An approach to Hang Seng index in Hong Kong stock market based on network topological statistics[J],Chinese Science Bulletin.2006,51(5):624-629
[13]庄新田,闵志峰等.上海证券市场的复杂网络特性分析[J],东北大学学报.2007,28(7):1053-1056
[14]邓超,陈学军.基于复杂网络的金融传染风险模型研究[J].中国管理科学,2014,22(11):11-18.
[15]欧阳红兵,刘晓东.中国金融机构的系统重要性及系统性风险传染机制分析[J].中国管理科学,2015,23(10):30-37.
[16]聂春笑,刘徽.股票网络的基尼系数[J].武汉理工大学学报,2013,(2):111-114.
[17]Yang Yue,Yang Huijie.Complex network-based time series analysis[J].Physics A,2008,387(5-6).1381-1386.
[18]Wang Jianbo,Yang Huijie.Complex network-based analysis of air temperature data in china[J].Modern physics letters,2009,23(14):1781-1789.
[19]Xu Xiaoke,Zhang Jie,Small M.Superfamily phenomena and motifs of networks induced from time series[J].Proc Natl Acad Sci USA,2008,105(50):19601-19605.
[20]Newman MEJ.The structure and function of complex networks[J].SIAM Rev,2003,45:167-256.
[21]Fortunato S.Community detection in graph[J].Phys Rep,2010,486:75-174.
[22]Kruskal J B.On the shortest spanning subtree of a graph and traveling salesman problem[J].Proceedings of the American Mathematical Society,1956,7(1):48-50.