Identification of crisis in the Chinese stock market based on complex network

In this article, we construct a Laplacian energy indicator to identify the financial crisis. Firstly, we use the Chinese A-shares market over the period from 2006 to 2017 to build complex networks year by year. Then, a network characteristic indicator based on Laplacian energy is built up to discern the subprime crisis, the European debt crisis and the Chinese stock market crash. The advantage of the proposed indicator lies in the fact that it has higher accuracy, less processing time, and better applicability, compared with the classical indicators such as average degree, modularity, average clustering coefficient, and characteristic path length.