The evolutionary stability of shareholders' co-holding behavior for China's listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks. (15th January 2016)

• Record Type: Journal Article
• Authors: Li, Huajiao; An, Haizhong; Huang, Jiachen; Huang, Xuan; Mou, Songtao; Shi, Yanli
• Is Part Of: Applied energy. Volume 162(2016)
• Page Start: 1601
• Page End: 1607
• Publication Date: 2016-01-15
• Subjects: Listed energy companies -- Evolutionary stability -- Co-holding behavior -- Holding-based network -- Maximal connected sub-graph -- Improved Heuristic Algorithm; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2015.04.049
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A novel method on studying relationships of listed energy companies' shareholders. A new perspective of studying the stability of energy stock market. An empirical study of the frontier of complex network-derivative equivalence network. Improved the Heuristic Algorithm to find the associated maximal connected sub-graph. A long term analysis about the evolutionary stability of China's energy stock market. Abstract: Listed energy companies play an important role in both the energy financial market and energy commodity market. As owners of listed energy companies, shareholders can influence the stability of the energy stock market by increasing or decreasing their holdings. To analyze the evolutionary features and stability of shareholders' co-holding behavior, we constructed a derivative holding-based structural equivalence network of the shareholders (holding-based network) based on the primitive shareholding network of the listed companies and their shareholders. The main data used in this paper are the semi-annual reports from 2003 to 2012 that contain information about Chinese listed energy companies' top 10 shareholders. The holding-based network takes the shareholders as nodes, whether holding the same listed energy companies' stock at the same time as the edges, and the number of listed energy companies co-held as the weights. Due to the unique topological features of the holding-based network, we improved the Heuristic Algorithm to find the associated maximal connected sub-graph of the network, which is the main group of shareholders with shareholding consistency of the listed energy companies. This paper creates a new approach to analyze the relationships in the energy stock market, presenting a new method to analyze shareholder behavior.