IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1004.4402.html
   My bibliography  Save this paper

Characteristics of Real Futures Trading Networks

Author

Listed:
  • Junjie Wang
  • Shuigeng Zhou
  • Jihong Guan

Abstract

Futures trading is the core of futures business, and it is considered as one of the typical complex systems. To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from the Shanghai Futures Exchange to construct futures trading networks, in which nodes are trading participants, and two nodes have a common edge if the two corresponding investors appear simultaneously in at least one trading record as a purchaser and a seller respectively. Then, we conduct a comprehensive statistical analysis on the constructed futures trading networks. Empirical results show that the futures trading networks exhibit features such as scale-free behavior with interesting odd-even-degree divergence in low-degree regions, small-world effect, hierarchical organization, power-law betweenness distribution, disassortative mixing, and shrinkage of both the average path length and the diameter as network size increases. To the best of our knowledge, this is the first work that uses real data to study futures trading networks, and we argue that the research results can shed light on the nature of real futures business.

Suggested Citation

  • Junjie Wang & Shuigeng Zhou & Jihong Guan, 2010. "Characteristics of Real Futures Trading Networks," Papers 1004.4402, arXiv.org, revised Feb 2011.
    • Handle: RePEc:arx:papers:1004.4402
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1004.4402
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fu, Feng & Liu, Lianghuan & Wang, Long, 2008. "Empirical analysis of online social networks in the age of Web 2.0," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 675-684.
    2. Zhou, Shuigeng & Hu, Guobiao & Zhang, Zhongzhi & Guan, Jihong, 2008. "An empirical study of Chinese language networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3039-3047.
    3. Stefano Battiston & Joao F. Rodrigues & Hamza Zeytinoglu, 2007. "The Network Of Inter-Regional Direct Investment Stocks Across Europe," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 29-51.
    4. S. M.G. Caldeira & T. C. Petit Lobão & R. F.S. Andrade & A. Neme & J. G.V. Miranda, 2006. "The network of concepts in written texts," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(4), pages 523-529, February.
    5. S. C. Wang & J. J. Tseng & C. C. Tai & K. H. Lai & W. S. Wu & S. H. Chen & S. P. Li, 2008. "Network topology of an experimental futures exchange," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(1), pages 105-111, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Han, Rui-Qi & Li, Ming-Xia & Chen, Wei & Zhou, Wei-Xing & Stanley, H. Eugene, 2019. "Structural properties of statistically validated empirical information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 747-756.
    3. 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.
    4. Ludvig Bohlin & Martin Rosvall, 2014. "Stock Portfolio Structure of Individual Investors Infers Future Trading Behavior," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-8, July.
    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. 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.
    7. 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.
    8. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    9. 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.
    10. Xie, Wen-Jie & Li, Mu-Yao & Zhou, Wei-Xing, 2021. "Learning representation of stock traders and immediate price impacts," Emerging Markets Review, Elsevier, vol. 48(C).
    11. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Ghosh, Dipak & Chakraborty, Sayantan & Samanta, Shukla, 2019. "Study of translational effect in Tagore’s Gitanjali using Chaos based Multifractal analysis technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1343-1354.
    3. Liang, Wei & Shi, Yuming & Huang, Qiuling, 2014. "Modeling the Chinese language as an evolving network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 268-276.
    4. Krawczyk, M.J. & Dydejczyk, A. & Kułakowski, K., 2014. "The Simmel effect and babies’ names," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 384-391.
    5. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, 2009. "Economic Networks: What Do We Know And What Do We Need To Know?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(04n05), pages 407-422.
    6. Peng, Dan & Han, Xiao-Pu & Wei, Zong-Wen & Wang, Bing-Hong, 2015. "Punctuated equilibrium dynamics in human communications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 36-44.
    7. Wenjia Liu & Jian Wang & Yanfeng Ouyang, 2022. "Rumor Transmission in Online Social Networks Under Nash Equilibrium of a Psychological Decision Game," Networks and Spatial Economics, Springer, vol. 22(4), pages 831-854, December.
    8. Antonios Garas & Athanasios Lapatinas & Konstantinos Poulios, 2016. "The Relation Between Migration And Fdi In The Oecd From A Complex Network Perspective," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 19(06n07), pages 1-20, September.
    9. Davi Alves Oliveira & Hernane Borges de Barros Pereira, 2024. "Modeling texts with networks: comparing five approaches to sentence representation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(6), pages 1-12, June.
    10. Kibae Kim & Jorn Altmann, 2013. "Evolution of the Software-as-a-Service Innovation System Through Collective Intelligence," TEMEP Discussion Papers 2013108, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Dec 2013.
    11. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    12. Li, Feng & Du, Timon Chih-ting & Wei, Ying, 2019. "Offensive pricing strategies for online platforms," International Journal of Production Economics, Elsevier, vol. 216(C), pages 287-304.
    13. Kibae Kim & Jorn Altmann, 2011. "A Complex Network Analysis of the Weighted Graph of the Web2.0 Service Network," TEMEP Discussion Papers 201178, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jul 2011.
    14. Jaime F. Lavin & Mauricio A. Valle & Nicolás S. Magner, 2019. "Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach," Complexity, Hindawi, vol. 2019, pages 1-20, July.
    15. Yang, Yi & Song, Yue, 2023. "Resistance-distance betweenness: Definition, properties, and application in complex linguistic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    16. Su, Qiang & Huang, Jiajia & Zhao, Xiande, 2015. "An information propagation model considering incomplete reading behavior in microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 55-63.
    17. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
    18. Junseok Hwang & Jorn Altmann & Kibae Kim, 2009. "The Structural Evolution of the Web2.0 Service Network," TEMEP Discussion Papers 200914, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Sep 2009.
    19. Liang, Wei & Chen, Guanrong, 2016. "Spectral analysis of Chinese language: Co-occurrence networks from four literary genres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 49-56.
    20. 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.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1004.4402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.