TY - JOUR
T1 - Comparison between global financial crisis and local stock disaster on top of Chinese stock network
AU - Xia, Lisi
AU - You, Daming
AU - Jiang, Xin
AU - Guo, Quantong
N1 - Publisher Copyright:
© 2017
PY - 2018/1/15
Y1 - 2018/1/15
N2 - The science of complex network theory can be usefully applied in many important fields, one of which is the finance. In these practical cases, a massive dataset can be represented as a very large network with certain attributes associated with its nodes and edges. As one of the most important components of financial market, stock market has been attracting more and more attention. In this paper, we propose a threshold model to build Chinese stock market networks and study the topological properties of these networks. To be specific, we compare the effects of different crises, namely the 2008 global crisis and the stock market disaster in 2015, on the threshold networks. Prices of the stocks belonging to the Shanghai and Shenzhen 300 index are considered for three periods: the global crisis, common period and the stock market disaster. We find the probability distribution of the cross-correlations of the stocks during the stock market disaster is fatter than that of others. Besides, the thresholds of cross-correlations are assigned to obtain the threshold networks and the power-law of degree distribution in these networks are observed in a certain range of threshold values. The networks during the stock market disaster also appear to have larger mean degree and modularity, which reveals the strong correlations among these stock prices. Our findings to some extent crosscheck the liquidity shortage reason which is believed to result in the outbreak of the stock market disaster. Moreover, we hope that this paper could give us a deeper understanding of the market's behavior and also lead to interesting future research about the problems of modern finance theory.
AB - The science of complex network theory can be usefully applied in many important fields, one of which is the finance. In these practical cases, a massive dataset can be represented as a very large network with certain attributes associated with its nodes and edges. As one of the most important components of financial market, stock market has been attracting more and more attention. In this paper, we propose a threshold model to build Chinese stock market networks and study the topological properties of these networks. To be specific, we compare the effects of different crises, namely the 2008 global crisis and the stock market disaster in 2015, on the threshold networks. Prices of the stocks belonging to the Shanghai and Shenzhen 300 index are considered for three periods: the global crisis, common period and the stock market disaster. We find the probability distribution of the cross-correlations of the stocks during the stock market disaster is fatter than that of others. Besides, the thresholds of cross-correlations are assigned to obtain the threshold networks and the power-law of degree distribution in these networks are observed in a certain range of threshold values. The networks during the stock market disaster also appear to have larger mean degree and modularity, which reveals the strong correlations among these stock prices. Our findings to some extent crosscheck the liquidity shortage reason which is believed to result in the outbreak of the stock market disaster. Moreover, we hope that this paper could give us a deeper understanding of the market's behavior and also lead to interesting future research about the problems of modern finance theory.
KW - Complex network
KW - Modularity
KW - Stock market disaster
KW - Stock price cross-correlation
KW - Threshold network
UR - https://www.scopus.com/pages/publications/85028500560
U2 - 10.1016/j.physa.2017.08.005
DO - 10.1016/j.physa.2017.08.005
M3 - 文章
AN - SCOPUS:85028500560
SN - 0378-4371
VL - 490
SP - 222
EP - 230
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -