Co-Movement in Stock Markets Based on Directed Complex Network


  •  Zhen Du    
  •  Pujiang Chen    
  •  Na Luo    
  •  Yingjie Tang    

Abstract

In this paper, directed complex network is applied to the study of A shares in SSE (Shanghai Stock Exchange). In order to discuss the intrinsic attributes and regularities in stock market, we set up a directed complex network, selecting 450 stocks as nodes between 2012 and 2014 and stock yield correlation connected as edges. By discussing out-degree and in-degree distribution, we find essential nodes in stock network, which represent the leading stock,. Moreover, we analyze directed average path length and clustering coefficient in the condition of different threshold, which shows that the network doesn’t have a small- world effect. Furthermore, we see that when threshold is between 0.08 and 0.15, the network follows the power-law distribution and behaves scale-free.



This work is licensed under a Creative Commons Attribution 4.0 License.