Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms

doi:10.1088/1674-1056/ab3f22

中国物理B ›› 2019, Vol. 28 ›› Issue (10): 108901-108901.doi: 10.1088/1674-1056/ab3f22

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇

Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms

Shi-Zhao Zhu(朱世钊), Yu-Qing Wang(王玉青), Bing-Hong Wang(汪秉宏)

1 School of Business, University of Shanghai for Science and Technology, Shanghai 200093, China;
2 School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China;
3 Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China

收稿日期:2019-04-04 修回日期:2019-07-15 出版日期:2019-10-05 发布日期:2019-10-05
通讯作者: Yu-Qing Wang, Bing-Hong Wang E-mail:yuqingw@hfut.edu.cn;bhwang@ustc.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 11705042 and 71874172), the China Postdoctoral Science Foundation (Grant Nos. 2018T110040 and 2016M590041), the Fundamental Research Funds for Central Universities, China (Grant No. JZ2018HGTB0238), Curriculum Planning and Design Research Project, China (Grant No. 102-033119), and the Teaching Quality and Teaching Reform Project, China (Grant No. JYQZ1815).

Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms

Shi-Zhao Zhu(朱世钊)¹, Yu-Qing Wang(王玉青)², Bing-Hong Wang(汪秉宏)^1,3

1 School of Business, University of Shanghai for Science and Technology, Shanghai 200093, China;
2 School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China;
3 Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China

Received:2019-04-04 Revised:2019-07-15 Online:2019-10-05 Published:2019-10-05
Contact: Yu-Qing Wang, Bing-Hong Wang E-mail:yuqingw@hfut.edu.cn;bhwang@ustc.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 11705042 and 71874172), the China Postdoctoral Science Foundation (Grant Nos. 2018T110040 and 2016M590041), the Fundamental Research Funds for Central Universities, China (Grant No. JZ2018HGTB0238), Curriculum Planning and Design Research Project, China (Grant No. 102-033119), and the Teaching Quality and Teaching Reform Project, China (Grant No. JYQZ1815).

摘要/Abstract

摘要： In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was not considered in the previous studies. In this work, a modified cross-correlation matrix that focuses on the influence of total asset on stock quote is introduced into the analysis of the stocks collected from Asian and American stock markets, which is different from the previous studies. The key results are obtained as follows. Firstly, stock is more greatly correlated with big asset than with small asset. Secondly, the higher the correlation coefficient among stocks, the larger the eigenvector is. Thirdly, in different periods, like the pre-subprime crisis period and the peak of subprime crisis period, Asian stock quotes show that the component of the third eigenvector of the cross-correlation matrix decreases with the asset of the enterprise decreasing. Fourthly, by simulating the threshold network, the small network constructed by 10 stocks with large assets can show the large network state constructed by 30 stocks. In this research we intend to fully explain the physical mechanism for understanding the historical correlation between stocks and provide risk control strategies in the future.

关键词: complex networks, total assets, subprime crisis, stock correlations

Abstract: In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was not considered in the previous studies. In this work, a modified cross-correlation matrix that focuses on the influence of total asset on stock quote is introduced into the analysis of the stocks collected from Asian and American stock markets, which is different from the previous studies. The key results are obtained as follows. Firstly, stock is more greatly correlated with big asset than with small asset. Secondly, the higher the correlation coefficient among stocks, the larger the eigenvector is. Thirdly, in different periods, like the pre-subprime crisis period and the peak of subprime crisis period, Asian stock quotes show that the component of the third eigenvector of the cross-correlation matrix decreases with the asset of the enterprise decreasing. Fourthly, by simulating the threshold network, the small network constructed by 10 stocks with large assets can show the large network state constructed by 30 stocks. In this research we intend to fully explain the physical mechanism for understanding the historical correlation between stocks and provide risk control strategies in the future.

Key words: complex networks, total assets, subprime crisis, stock correlations

中图分类号: (Economics; econophysics, financial markets, business and management)

89.65.Gh

89.75.-k (Complex systems)

朱世钊, 王玉青, 汪秉宏. Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms[J]. 中国物理B, 2019, 28(10): 108901-108901.

Shi-Zhao Zhu(朱世钊), Yu-Qing Wang(王玉青), Bing-Hong Wang(汪秉宏). Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms[J]. Chin. Phys. B, 2019, 28(10): 108901-108901.

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Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms

Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms

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