Research On The Characteristics Of Shanghai Stock Market

In recent years,the stock market in China had a great volatility phase.In this context,by a new views of network analysis,we use social network analysis method to establish stock market correlation network based on 307 stock’s weekly closing prize in shanghai,and analyzed its’ structure.The specific content and conclusions are as follows:In the analysis on Centrality,by indicator for degree,betweenness and closeness centrality,we respectively analyzed centrality for Shanghai correlation network and wholesale retail industry correlation network.Then we compare their centrality analysis results.The results shows that the same kind of stock may play different roles in different stock correlation network.On the basis of the study above,by comparing three centrality indicators,we can find out the special stocks,whose three centrality indicators are inconsistent and give some suggestions for the special stocks’ investments.In the analysis on cohesive subgroups,the paper starts from 2-faction,k-cluster,block model and industry attracting rate respectively to carry out research and discussion on the stock-related network of Shanghai Stock Exchange and retailing wholesale industry.The conclusion as follows:(1)Stocks of higher centrality come with larger number of cohesive subgroups connected to them;(2)The stocks in the same K group stage are from the same industry,or the stocks in the same K group stage are closely correlated;(3)Shanghai correlation network can be partitioned into 7blocks and the stocks in the first,third,fifth and the seventh partitions are strongly correlated.To enhance the pertinence of analysis,the analysis shall be solely launched of partition while investing the stocks in the second,fourth and the sixth partitions.(4)the retailing wholesale industry and construction industry share the most closely connection with other industries,indicating that these two industries have a great impact on the stock market of the Shanghai Stock Exchange.In analysis on small-world characteristics,We verify whether the network has the characteristics of small-world by measuring indicators of feature length and clustering coefficient,and then compare the measuring results with that of the same scale ER random network.The results show that the characteristic path length of the correlation network is nearly equal to that of the ER random network,but the clustering coefficient of the correlation network is much larger than that of the ER random network,which is consistent with the characteristics of the small-world network.