Research On Energy Stocks Market Associated Network Evolution Characteristics Based On Financial Indicators

Energy financial market is a complex system consisting of many interacting units.Energy stocks market as an important part of energy financial markets,is a thermometer in the economic development of the national energy.Energy listed companies are major players in the energy stock market,in recent years,the number of listed energy companies has been increasing.The financial indicators can objectively and comprehensively reflect a company's financial ability,which can strongly prove the intrinsic value of the stock.The financial indicators comprehensively and objectively reflect a company's financial ability,which can strongly prove the intrinsic value of the stock.By describing the relationship between stocks through a series of financial indicators,we can learn more about the energy stock market relationship.Complex networks theory is a powerful tool to analyze the topological structure characteristics and the stock market problem.Therefore,this paper combines the theory of complex networks and statistical theory to study the characteristics and evolution rules of stock-associated networks based on the financial indicators of listed companies.In this paper,the financial data of 77 Listed Company in the China Securities Index in the Wind Information Database are selected as sample data.Data selection time range from 2011 to 2015.123 financial indicators were selected to build a financial index system of energy listed companies.Then,we normalize financial indicator data of each listed company to the same dimension,we calculate the structural similarity coefficient of financial indicators of every two listed company and build structure similarity matrix of 77×77.On this basis,we take stock as the node and the similarity coefficient of financial structure as the edge,and build stock associated network models of different time scales and different threshold scenarios.The detailed analysis of the closeness and similarity scope of the nodes,cohesion strength of nodes and community are carried out.The study found that:(1)Under different threshold scenarios,the structural characteristics of the network are greatly different.Threshold value 0.7 is the mutation point of the network.Pay attention to the evolution of the network structure before and after the threshold and excavate more stock market information.;On the time scale,due to the similarity in the financial model and operation of energy stocks,the financial similarity among stocks has been increasing year by year.(2)The trend of community of energy stock associated network is significant and community distribution has a great relationship with the region and the industry nature.Different energy stocks have different development trends.The oil and coal industries' stocks have a single financial development model,and the manufacturing industry's stocks have a diversified financial development mode.(3)There are key stock nodes in different communities.The financial indicators structures of these stocks are quite different.When faced with changes in the external environment,different financial policies will be adopted,so the financial structure of the stock nodes of different communities must be kept in focus.These findings provide guidance for optimizing the financial structure of energy companies and diversifying investors' investments.