Research On The Topological Characteristics And Robustness Of Chinese Real Estate Credit Network

Chinese Real Estate finance is a giant and complex system which regards houses as the carrier, real estate enterprises and financial institutions as direct main body and the government as indirect body. It is related to the production, circulation and consumption, so it has an important impact on the the economic, social and ecological environment in all aspects of China. It has a crucial influence on Chinese Real Estate industry to improve the Financing Structure of Chinese Real Estate and optimize the credit resources allocation from the macro perspective. Meanwhile, it is beneficial to create the mutual promotion and win-win situation from the micro perspective.In fact, Financing Structure of Chinese Real Estate essentially reflects the resources allocation of Estate Finance. And amount of individual behavior can spring up macro structure. So it is a basic requirement of the socialist system to study the relationship between real estate enterprises and financial institutions, which can benefit the resources allocation in financial market and improve the efficiency of resource utilization.In this dissertation, based on complex network theory, a bipartite network whose nodes are divided into listed real estate companies and financial institutions is created with the long-term borrowing information between them, using the data of listed companies in real estate industry from Shanghai Stock Exchange and Shenzhen Stock Exchange. Through the projection method, we get a weighted real estate credit network. Then the topological characteristics and robustness of Chinese Real Estate Credit Network is studied to find the evolution law and anti-shock function of the credit network. On the one side, the network’s basic topological characteristics is analyzed, such as Small-world effect, Scale-free feature, Degree Correlation and Centrality. Empirical study shows that Chinese Real Estate Credit Network is a Small-world network, but not Scale-free network with the power law between 2007 and 2013. With the expanding of network scale, the new nodes are inclined to connect with nodes whose degree are larger than others. Meanwhile, five state-owned banks and joint-stock banks play pivotal role in the real estate credit network, which has important effect on the stability of network. On the other side, in order to study the robustness of this credit network, the strategy of random attack and selective attack are used. Measurement indicators include the largest component of the network(W),Clustering Coefficient(C)and Average Path Length(L). Empirical study shows that the robustness of Chinese Real Estate Credit Network is poor. In addition,selective attack is significantly greater than random attack when attacking the network.From the complex network perspective, the analysis of the topological characteristics and robustness of Chinese Real Estate Credit Network helps to build communication bridges between the micro and macro of Chinese Real Estate financial market, as well as to innovate the research paradigm in the field of Chinese Real Estate finance.