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

机译:中国新能源股市的拓扑结构分析:多维数据网络视角

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摘要

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.
机译:在本文中,我们应用RV系数网络,通过2012年1月4日至2019年3月29日期间CSI(中国股票指数)新能源指数的60只成份股的每日价格,研究了中国新能源股票市场的拓扑结构。与皮尔逊相关系数相比,RV系数能更好地从多维数据的角度反映股票之间的相似性。实证结果表明:(1)中国新能源股票市场的无标度特征不显著;(2) 新能源存储是新能源行业的主导子行业,新能源互动设备在可再生能源生产和新能源存储之间起着连接作用;(3) 网络中最具影响力的股票是集团DMEGC磁性有限公司、厦门钨业有限公司和GEM有限公司,它们在网络连接中发挥着重要作用。这些发现对于理解中国新能源股票与股票定价机制之间的相互作用具有重要意义。当局应该更加关注新能源存储行业。投资者的投资组合可以根据股票和子行业的影响评估进行优化。

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