TOPOLOGICAL STRUCTURAL ANALYSIS OF CHINA'S NEW ENERGY STOCK MARKET: A MULTI-DIMENSIONAL DATA NETWORK PERSPECTIVE

Author:

Yin Kedong1,Liu Zhe2,Huang Chong2,Liu Peide3

Affiliation:

1. School of Economics, Ocean University of China, 266100 Qingdao Shandong, China; Ocean Development Research Institute, Major Research Base of Humanities and Social Sciences of Ministry of Education, Ocean University of China, 266100 Qingdao Shandong, China

2. School of Economics, Ocean University of China, 266100 Qingdao Shandong, China

3. School of Management Science and Engineering, Shandong University of Finance and Economics, 250014 Jinan Shandong, China

Abstract

In this paper, we apply an RV coefficient network to investigate the topological structure of China’s new energy stock market via daily prices of 60 component stocks of CSI (China Stock Index) New Energy Index spanning the period January 4, 2012 to March 29, 2019. Compared with the Pearson correlation coefficient, RV coefficient can better reflect the similarity between stocks from the perspective of multi-dimensional data. The empirical result indicates that (1) the scale-free characteristics of China’s new energy stock market are not significant; (2) the new energy storage is the leading sub-sector of the new energy sector and the new energy interactive equipment plays a connecting role between renewable energy production and new energy storage; (3) the most influential stock in the network is Group DMEGC Magnetics Co., Ltd., Xiamen Tungsten Co., Ltd. and GEM Co., Ltd. play an important role in the network connection. These findings are of great significance to understand the interaction between Chinese new energy stocks and the pricing mechanism of stocks. The authority should pay more attention to the new energy storage industry. Investor’s portfolios can be optimized according to the influence assessment of stocks and sub-sectors.

Publisher

Vilnius Gediminas Technical University

Subject

Finance

Reference58 articles.

1. THE RURAL SUSTAINABLE DEVELOPMENT THROUGH RENEWABLE ENERGY. THE CASE OF ROMANIA

2. A Random Graph Model for Power Law Graphs

3. Statistical mechanics of complex networks

4. Correlation structure and dynamics in volatile markets

5. Bloomberg New Energy Finance. (2018). Global trends in renewable energy investment 2018. UNEP United Nations Environment Programme, Bloomberg New Energy Finance. http://www.iberglobal.com/files/2018/renewable_trends.pdf

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