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A network perspective of comovement and structural change: Evidence from the Chinese stock market
Huang, Chuangxia1,2; Deng, Yunke1,2; Yang, Xiaoguang3; Cao, Jinde4,5; Yang, Xin1,2
2021-07-01
Source PublicationINTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
ISSN1057-5219
Volume76Pages:18
AbstractHow to appropriately characterize the comovement between any pair of individual stocks and describe the market comovement structure is a great challenge and plays a key role in understanding emerging markets. This paper applies the complex network approach to deal with this issue for the Chinese stock market. Firstly, in view of the topological properties, we investigate the time-varying comovement between individual stocks by constructing 14 directed weighted stock networks. Furthermore, the weighted LeaderRank algorithm is employed to describe the comovement structure of the entire market. Most importantly, from the perspective of fundamental factors and industry factors, we reveal the driving factors of the comovement and structural change of the entire market. The empirical results suggest that: (i) Stocks with higher weighted LeaderRank algorithm scores generally have more long-term investment value; and the so-called views, "too big to fail"and "too connected to fail", are further confirmed. (ii) ROE, BMratio and Growth are significantly positively correlated with the comovement between individual stocks, and Mvalue is significantly negatively correlated during normal periods. However, during the crisis, the signs of regression coefficients of above four explanatory variables are reversed. (iii) In normal periods, we only find that the agriculture, forestry, animal husbandry & fishery and composite have significant influence on the comovement structure of the entire market. Besides, public utilities and medias also have a significant impact during the crisis. In addition, a very interesting fact in point is that network density, average clustering coefficient, and global efficiency can provide an "early warning"for possible upcoming crises.
KeywordChinese stock market Comovement Complex network Engle-Granger test Weighted LeaderRank algorithm
DOI10.1016/j.irfa.2021.101782
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[71850008] ; National Natural Science Foundation of China[71471020] ; Natural Science Foundation of Hunan Province, China[2019JJ50650] ; Scientific Research Foundation of Hunan Provincial Education Department, China[18C0221]
WOS Research AreaBusiness & Economics
WOS SubjectBusiness, Finance
WOS IDWOS:000670127400016
PublisherELSEVIER SCIENCE INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/58888
Collection中国科学院数学与系统科学研究院
Corresponding AuthorYang, Xin
Affiliation1.Changsha Univ Sci & Technol, Sch Math & Stat, Changsha, Peoples R China
2.Hunan Prov Key Lab Math Modeling & Anal Engn, Changsha 410114, Hunan, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100864, Peoples R China
4.Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
5.Yonsei Univ, Yonsei Frontier Lab, Seoul 03722, South Korea
Recommended Citation
GB/T 7714
Huang, Chuangxia,Deng, Yunke,Yang, Xiaoguang,et al. A network perspective of comovement and structural change: Evidence from the Chinese stock market[J]. INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS,2021,76:18.
APA Huang, Chuangxia,Deng, Yunke,Yang, Xiaoguang,Cao, Jinde,&Yang, Xin.(2021).A network perspective of comovement and structural change: Evidence from the Chinese stock market.INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS,76,18.
MLA Huang, Chuangxia,et al."A network perspective of comovement and structural change: Evidence from the Chinese stock market".INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS 76(2021):18.
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