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Complex stock trading network among investors

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  • Zhi-Qiang Jiang

    (ECUST)

  • Wei-Xing Zhou

    (ECUST)

Abstract

We provide an empirical investigation aimed at uncovering the statistical properties of intricate stock trading networks based on the order flow data of a highly liquid stock (Shenzhen Development Bank) listed on Shenzhen Stock Exchange during the whole year of 2003. By reconstructing the limit order book, we can extract detailed information of each executed order for each trading day and demonstrate that the trade size distributions for different trading days exhibit power-law tails and that most of the estimated power-law exponents are well within the L{\'e}vy stable regime. Based on the records of order matching among investors, we can construct a stock trading network for each trading day, in which the investors are mapped into nodes and each transaction is translated as a direct edge from the seller to the buyer with the trade size as its weight. We find that all the trading networks comprise a giant component and have power-law degree distributions and disassortative architectures. In particular, the degrees are correlated with order sizes by a power-law function. By regarding the size executed order as its fitness, the fitness model can reproduce the empirical power-law degree distribution.

Suggested Citation

  • Zhi-Qiang Jiang & Wei-Xing Zhou, 2010. "Complex stock trading network among investors," Papers 1003.2459, arXiv.org, revised May 2010.
  • Handle: RePEc:arx:papers:1003.2459
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    References listed on IDEAS

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    1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
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    Cited by:

    1. repec:eee:ememar:v:34:y:2018:i:c:p:143-161 is not listed on IDEAS
    2. Li, Jie & Ren, Da & Feng, Xu & Zhang, Yongjie, 2016. "Network of listed companies based on common shareholders and the prediction of market volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 508-521.
    3. Ming-Xia Li & Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Wei-Xing Zhou, 2013. "Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant," Papers 1308.0925, arXiv.org.
    4. Behfar, Stefan Kambiz & Turkina, Ekaterina & Cohendet, Patrick & Burger-Helmchen, Thierry, 2016. "Directed networks’ different link formation mechanisms causing degree distribution distinction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 479-491.
    5. Zhao, Zheng & Zhang, YongJie & Feng, Xu & Zhang, Wei, 2014. "An analysis of herding behavior in security analysts’ networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 116-124.
    6. Sun, Xiao-Qian & Shen, Hua-Wei & Cheng, Xue-Qi & Zhang, Yuqing, 2017. "Detecting anomalous traders using multi-slice network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 1-9.
    7. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised May 2018.
    8. Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
    9. Yang, Chunxia & Chen, Yanhua & Niu, Lei & Li, Qian, 2014. "Cointegration analysis and influence rank—A network approach to global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 168-185.
    10. repec:eee:appene:v:207:y:2017:i:c:p:477-493 is not listed on IDEAS
    11. Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Yong-Jie Zhang & W. -X. Zhou, 2012. "Trading networks, abnormal motifs and stock manipulation," Papers 1301.0007, arXiv.org.
    12. Arshad, Shaista & Rizvi, Syed Aun R. & Ghani, Gairuzazmi Mat & Duasa, Jarita, 2016. "Investigating stock market efficiency: A look at OIC member countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 402-413.
    13. Xiao-Qian Sun & Xue-Qi Cheng & Hua-Wei Shen & Zhao-Yang Wang, 2011. "Distinguishing manipulated stocks via trading network analysis," Papers 1110.2260, arXiv.org.
    14. Zhang, Yongjie & Cao, Xing & He, Feng & Zhang, Wei, 2017. "Network topology analysis approach on China’s QFII stock investment behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 77-88.
    15. Li, Huajiao & An, Haizhong & Fang, Wei & Wang, Yue & Zhong, Weiqiong & Yan, Lili, 2017. "Global energy investment structure from the energy stock market perspective based on a Heterogeneous Complex Network Model," Applied Energy, Elsevier, vol. 194(C), pages 648-657.
    16. Sun, Xiao-Qian & Cheng, Xue-Qi & Shen, Hua-Wei & Wang, Zhao-Yang, 2011. "Distinguishing manipulated stocks via trading network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3427-3434.
    17. Chen, Kun & Luo, Peng & Sun, Bianxia & Wang, Huaiqing, 2015. "Which stocks are profitable? A network method to investigate the effects of network structure on stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 224-235.
    18. Alam, Nafis & Arshad, Shaista & Rizvi, Syed Aun R., 2016. "Do Islamic stock indices perform better than conventional counterparts? An empirical investigation of sectoral efficiency," Review of Financial Economics, Elsevier, vol. 31(C), pages 108-114.
    19. Li, Ming-Xia & Jiang, Zhi-Qiang & Xie, Wen-Jie & Xiong, Xiong & Zhang, Wei & Zhou, Wei-Xing, 2015. "Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 575-584.
    20. repec:kap:compec:v:51:y:2018:i:3:d:10.1007_s10614-016-9627-7 is not listed on IDEAS

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