Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network
文献类型：期刊论文
| 作者 | Huang, Chuangxia1; Zhao, Xian1; Deng, Yunke1; Yang, Xiaoguang2; Yang, Xin1 |
| 刊名 | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
 |
| 出版日期 | 2022-03-01 |
| 卷号 | 78页码:81-94 |
| 关键词 | Complex network Chinese energy stock market High-frequency data Jump volatility Entropy weight TOPSIS |
| ISSN号 | 1059-0560 |
| DOI | 10.1016/j.iref.2021.11.001 |
| 英文摘要 | We employ a complex network approach to dig out the influential Chinese energy stocks in this paper. We first use the 5-min high-frequency data of the Chinese energy stocks over the period of 2013-2018 to build a static jump volatility spillover network. Then a novel method of entropy weight TOPSIS (Technique for Order Preference by Similarities to Ideal Solution) is proposed to evaluate the influential nodes. Furthermore, we construct dynamic networks with the help of time-varying Granger causality test. Empirical analyses show that: (1) Combining static network and the proposed entropy weight TOPSIS scores, we find that China Petroleum Engineering & Construction Corp, Zhengzhou Coal Industry & Electric Power Co.,Ltd., Shenzhen Guangju Energy Co.,Ltd., China Coal Energy Company Limited and Shaanxi Provincial Natural Gas Co.,Ltd. are influential energy stocks. (2) The advantage of entropy weight TOPSIS lies in the fact that it has the highest correlation coefficient between its score and jump volatility is the highest, comparing with the traditional methods such as equal weight, TOPSIS, analytic hierarchy process and principal component analysis. (3) Particularly, by making full use of dynamic network analysis, a very interesting finding in this paper indicates that the network density also provides an "early warning" for possible upcoming crises. (4) In addition, a very interesting fact in point is that most of the stocks with larger market capitalization usually have high-level influence during Chinese stock market crash; such smallcapitalization energy stocks with high scores are however particularly crucial for investors and regulatory authorities to grasp the risk characteristic. The results can provide us some light for finding out those influential energy stocks whose volatilities may cause many other stocks in the energy industry to rise and fall. |
| WOS研究方向 | Business & Economics |
| 语种 | 英语 |
| WOS记录号 | WOS:000744227300004 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/59914]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Yang, Xin |
| 作者单位 | 1.Changsha Univ Sci & Technol, Sch Math & Stat, Hunan Prov Key Lab Math Modeling & Anal Engn, Changsha 410114, Hunan, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100864, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Chuangxia,Zhao, Xian,Deng, Yunke,et al. Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network[J]. INTERNATIONAL REVIEW OF ECONOMICS & FINANCE,2022,78:81-94. |
| APA | Huang, Chuangxia,Zhao, Xian,Deng, Yunke,Yang, Xiaoguang,&Yang, Xin.(2022).Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network.INTERNATIONAL REVIEW OF ECONOMICS & FINANCE,78,81-94. |
| MLA | Huang, Chuangxia,et al."Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network".INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 78(2022):81-94. |
入库方式： OAI收割
来源：数学与系统科学研究院
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