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

  • Regular Article - Statistical and Nonlinear Physics
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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”.

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Data Availability Statement

This manuscript has no associated data or the data will not be deposited. [Authors’ comment: The data used to support the findings of this study are available from the corresponding author upon request.]

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Acknowledgements

We wish to express our gratitude to the referees for their invaluable comments and suggestions. This research is supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant number KYCX19_0130) and Scientific Research Foundation of Graduate School of Southeast University (Grant number YBPY1942).

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Authors and Affiliations

  1. School of Economics and Management, Southeast University, Nanjing, 211189, China

    Zicheng Pan, Junfei Ding & Lei Wang

  2. College of Finance, Nanjing Agricultural University, Nanjing, 210095, China

    Qianting Ma

Authors
  1. Zicheng Pan
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  2. Qianting Ma
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  3. Junfei Ding
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  4. Lei Wang
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Contributions

ZP: conceptualization; data curation, and writing—original draft preparation. QM: formal analysis and methodology. JD: conceptualization, investigation, methodology, and writing—review & editing. LW: software, formal analysis, and funding acquisition. Additionally, ZP and LW have contributed equally to this work. They are co-first authors.

Corresponding author

Correspondence to Junfei Ding.

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The authors declare that there is no conflict of interest.

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Pan, Z., Ma, Q., Ding, J. et al. Research on the stock correlation networks and network entropies in the Chinese green financial market. Eur. Phys. J. B 94, 56 (2021). https://doi.org/10.1140/epjb/s10051-021-00063-5

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  • DOI: https://doi.org/10.1140/epjb/s10051-021-00063-5

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