A New Method For Dynamic Stock Clustering Based On Spectral Analysis

doi:10.1007/s10614-016-9589-9

	A New Method For Dynamic Stock Clustering Based On Spectral Analysis
	Li, Zhaoyuan ; Tian, Maozai1,3,4
	2017-10
发表期刊	COMPUTATIONAL ECONOMICS
卷号	50 期号:3 页码:373-392
摘要	In this paper, we propose a new method to classify the stock cluster based on the motions of stock returns. Specifically, there are three criteria: The positive or negative signs of elements in the eigenvector of correlation matrix indicate the response direction of individual stocks. The components are included based on the sequence of corresponding eigenvalue magnitudes from large to small. All the elements in the cluster representing individual stocks should have same signs across the components included in the classification process. With the number of vectors included in the process increasing, a speed-up process for cluster number is identified. We interpret this phenomenon as a phase transition from a state dominated by meaningful information to one dominated by trivial information. And a critical point exists in this process. The sizes of clusters near this critical point can be regarded as a power law distribution. The critical exponent evolvement indicates structure of the market. The vector number at this point can be adopted to classify the stock clusters. We analyze the cross-correlation matrices of stock logarithm returns of both China and US stock market for the period from January 4, 2005 to December 31, 2010. The period includes the anomalies time of financial crisis. The number of clusters in financial and technology sectors is further examined to reveal the varying feather of traditional industries. Distinct patterns of industrial differentiation between China and US have been found according to our study.
关键词	Stock return Cross-correlation Stock cluster Phase transition Spectral Analysis
DOI	10.1007/s10614-016-9589-9
收录类别	SCI ; SCOPUS ; SCIE ; SSCI
ISSN	0927-7099
语种	英语
WOS研究方向	Business & Economics ; Mathematics
WOS类目	Economics ; Management ; Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000408202600002
出版者	SPRINGER
原始文献类型	Article
EISSN	1572-9974
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/11772
专题	统计与数据科学学院
作者单位	1.Renmin Univ China, Sch Stat, Ctr Appl Stat, Beijing 100872, Peoples R China; 2.Univ Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R China; 3.Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou, Gansu, Peoples R China; 4.Xinjiang Univ Finance & Econ, Sch Stat & Informat, Urumqi, Peoples R China
推荐引用方式 GB/T 7714	Li, Zhaoyuan,Tian, Maozai. A New Method For Dynamic Stock Clustering Based On Spectral Analysis[J]. COMPUTATIONAL ECONOMICS,2017,50(3):373-392.
APA	Li, Zhaoyuan,&Tian, Maozai.(2017).A New Method For Dynamic Stock Clustering Based On Spectral Analysis.COMPUTATIONAL ECONOMICS,50(3),373-392.
MLA	Li, Zhaoyuan,et al."A New Method For Dynamic Stock Clustering Based On Spectral Analysis".COMPUTATIONAL ECONOMICS 50.3(2017):373-392.

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