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Adaptive financial networks with static and dynamic thresholds

Author

Listed:
  • Tian Qiu
  • Bo Zheng
  • Guang Chen

Abstract

Based on the daily data of American and Chinese stock markets, the dynamic behavior of a financial network with static and dynamic thresholds is investigated. Compared with the static threshold, the dynamic threshold suppresses the large fluctuation induced by the cross-correlation of individual stock prices, and leads to a stable topological structure in the dynamic evolution. Long-range time-correlations are revealed for the average clustering coefficient, average degree and cross-correlation of degrees. The dynamic network shows a two-peak behavior in the degree distribution.

Suggested Citation

  • Tian Qiu & Bo Zheng & Guang Chen, 2010. "Adaptive financial networks with static and dynamic thresholds," Papers 1002.3432, arXiv.org.
  • Handle: RePEc:arx:papers:1002.3432
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    File URL: http://arxiv.org/pdf/1002.3432
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    Cited by:

    1. Sun, Mei & Li, Juan & Gao, Cuixia & Han, Dun, 2017. "Identifying regime shifts in the US electricity market based on price fluctuations," Applied Energy, Elsevier, vol. 194(C), pages 658-666.
    2. Chunxia, Yang & Bingying, Xia & Sen, Hu & Rui, Wang, 2012. "A study of the interplay between the structure variation and fluctuations of the Shanghai stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3198-3205.
    3. repec:kap:compec:v:51:y:2018:i:2:d:10.1007_s10614-017-9672-x is not listed on IDEAS
    4. 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.
    5. 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 Sep 2017.
    6. Frank Emmert-Streib & Aliyu Musa & Kestutis Baltakys & Juho Kanniainen & Shailesh Tripathi & Olli Yli-Harja & Herbert Jodlbauer & Matthias Dehmer, 2017. "Computational Analysis of the structural properties of Economic and Financial Networks," Papers 1710.04455, arXiv.org.
    7. 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.
    8. Jun-jie Chen & Bo Zheng & Lei Tan, 2014. "Agent-based model with asymmetric trading and herding for complex financial systems," Papers 1407.5258, arXiv.org.
    9. repec:eee:phsmap:v:493:y:2018:i:c:p:301-310 is not listed on IDEAS
    10. 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.
    11. X. F. Jiang & T. T. Chen & B. Zheng, 2013. "Time-reversal asymmetry in financial systems," Papers 1308.0669, arXiv.org.
    12. repec:eee:phsmap:v:482:y:2017:i:c:p:337-344 is not listed on IDEAS
    13. Jiang, X.F. & Chen, T.T. & Zheng, B., 2013. "Time-reversal asymmetry in financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5369-5375.
    14. Hu, Sen & Yang, Hualei & Cai, Boliang & Yang, Chunxia, 2013. "Research on spatial economic structure for different economic sectors from a perspective of a complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3682-3697.

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