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Antinetwork among China A-shares

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  • Peng Liu

Abstract

The correlation-based financial networks, constructed with the correlation relationships among the time series of fluctuations of daily logarithmic prices of stocks, are intensively studied. However, these studies ignore the importance of negative correlations. This paper is the first time to consider the negative and positive correlations separately, and accordingly to construct weighted temporal antinetwork and network among stocks listed in the Shanghai and Shenzhen stock exchanges. For (anti)networks during the first 24 years of the 21st century, the node's degree and strength, the assortativity coefficient, the average local clustering coefficient, and the average shortest path length are analyzed systematically. This paper unveils some essential differences in these topological measurements between antinetwork and network. The findings of the differences between antinetwork and network have an important role in understanding the dynamics of a financial complex system. The observation of antinetwork is of great importance in optimizing investment portfolios and risk management. More importantly, this paper proposes a new direction for studying complex systems, namely the correlation-based antinetwork.

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  • Peng Liu, 2024. "Antinetwork among China A-shares," Papers 2404.00028, arXiv.org.
    • Handle: RePEc:arx:papers:2404.00028
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    References listed on IDEAS

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    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. Liu, Peng & Zheng, Yanyan, 2022. "Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    4. M. Tumminello & T. Di Matteo & T. Aste & R. N. Mantegna, 2007. "Correlation based networks of equity returns sampled at different time horizons," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 209-217, January.
    5. Qiao Jiang & Qianting Ma & Xiaoxing Liu, 2021. "Research on the Stock Correlation Network Entropy and Its Influencing Factors in the Chinese Interbank Market," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-8, July.
    6. J.-P. Onnela & K. Kaski & J. Kertész, 2004. "Clustering and information in correlation based financial networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 353-362, March.
    7. 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.
    8. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
    9. Irena Vodenska & Alexander P. Becker & Di Zhou & Dror Y. Kenett & H. Eugene Stanley & Shlomo Havlin, 2016. "Community Analysis of Global Financial Markets," Risks, MDPI, vol. 4(2), pages 1-15, May.
    10. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    11. Seung Wook Oh & Julie A. Harris & Lydia Ng & Brent Winslow & Nicholas Cain & Stefan Mihalas & Quanxin Wang & Chris Lau & Leonard Kuan & Alex M. Henry & Marty T. Mortrud & Benjamin Ouellette & Thuc Ngh, 2014. "A mesoscale connectome of the mouse brain," Nature, Nature, vol. 508(7495), pages 207-214, April.
    12. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.
    13. Diego Garlaschelli & Guido Caldarelli & Luciano Pietronero, 2003. "Universal scaling relations in food webs," Nature, Nature, vol. 423(6936), pages 165-168, May.
    14. Xia, Lisi & You, Daming & Jiang, Xin & Guo, Quantong, 2018. "Comparison between global financial crisis and local stock disaster on top of Chinese stock network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 222-230.
    15. Conte, Marc N. & Kelly, David L., 2018. "An imperfect storm: Fat-tailed tropical cyclone damages, insurance, and climate policy," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 677-706.
    16. Peng Liu & Yanyan Zheng, 2022. "Precision measurement of the return distribution property of the Chinese stock market index," Papers 2209.08521, arXiv.org, revised Nov 2023.
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