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Research on the stock correlation networks and network entropies in the Chinese green financial market

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  • Zicheng Pan

    (Southeast University)

  • Qianting Ma

    (Nanjing Agricultural University)

  • Junfei Ding

    (Southeast University)

  • Lei Wang

    (Southeast University)

Abstract

Green financial stock is an important embodiment of the social sustainable value. The complex network theory provides an important research paradigm for studying the stock correlations and the dynamic evolution characteristics in the green financial market. Considering that a few scholars have studied the green financial network, we fill this gap by constructing the stock correlation network model based on the correlations of stock price fluctuations to analyze the network centrality and its influencing factors in the Chinese green financial market. Subsequently, it is also applied to explore the dynamic evolution characteristics of the stock correlation networks and the correlations between the network structures and different types of network entropies in the Chinese green financial market. In the light of empirical research, we can obtain the following results. First, the variables about corporate sustainable development, corporate green innovation output, corporate social responsibility, corporate return on net assets, and corporate property rights play positive roles in promoting the network centrality ranking of individual enterprises in the stock correlation networks of the Chinese green financial market, while the corporate age is negatively related to the network centrality ranking. Second, the stock correlation networks of the Chinese green financial market show the small-world feature in the dynamic evolution process. Third, network entropies can effectively depict the change direction of network structures over time in the Chinese green financial market. Finally, to maintain the stable operation of the green financial market, more and more importance is attached by the regulatory authorities to these green financial stocks that are “too related to fail”. Graphic abstract

Suggested Citation

  • Zicheng Pan & Qianting Ma & Junfei Ding & Lei Wang, 2021. "Research on the stock correlation networks and network entropies in the Chinese green financial market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(2), pages 1-11, February.
    • Handle: RePEc:spr:eurphb:v:94:y:2021:i:2:d:10.1140_epjb_s10051-021-00063-5
    DOI: 10.1140/epjb/s10051-021-00063-5
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    1. Liu, Chen & Li, Xuefei, 2019. "Media coverage and investor scare behavior diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
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