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Mechanism of investor behavior propagation in stock market

Author

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  • Nian, Fuzhong
  • Liu, Xinghao
  • Diao, Hongyuan

Abstract

Investor behavior has a pivotal role in price dynamics. The aim of this study was to explore the characteristics and patterns of the investor behavior and network structure behind. The investor behavior propagation model was proposed, which described the intrinsic dynamic mechanism of stock market and had a good fit to the real data. It was found that the Nearest-neighbor coupled network and the disassortative network can depict the investing behavior network precisely. Combining these two aspects, the Nearest-neighbor coupled network with hub nodes was constructed. Performance was superior to other network structures and suggests that the Nearest-neighbor coupled network with hub nodes is more consistent with the real investor networks.

Suggested Citation

  • Nian, Fuzhong & Liu, Xinghao & Diao, Hongyuan, 2022. "Mechanism of investor behavior propagation in stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    • Handle: RePEc:eee:phsmap:v:608:y:2022:i:p1:s0378437122008299
    DOI: 10.1016/j.physa.2022.128271
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    References listed on IDEAS

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    1. Zoran Ivkovi & Scott Weisbenner, 2007. "Information Diffusion Effects in Individual Investors' Common Stock Purchases: Covet Thy Neighbors' Investment Choices," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1327-1357.
    2. Horst, Ulrich & Scheinkman, Jose A., 2006. "Equilibria in systems of social interactions," Journal of Economic Theory, Elsevier, vol. 130(1), pages 44-77, September.
    3. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 15(2), pages 457-510.
    4. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    5. Giulia Iori, 1999. "Avalanche Dynamics And Trading Friction Effects On Stock Market Returns," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 10(06), pages 1149-1162.
    6. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    7. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2013. "Minority Games: Interacting agents in financial markets," OUP Catalogue, Oxford University Press, number 9780199686698, Decembrie.
    8. P. Gopikrishnan & M. Meyer & L.A.N. Amaral & H.E. Stanley, 1998. "Inverse cubic law for the distribution of stock price variations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 3(2), pages 139-140, July.
    9. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    10. Benoit Mandelbrot, 1963. "New Methods in Statistical Economics," Journal of Political Economy, University of Chicago Press, vol. 71, pages 421-421.
    11. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2004. "Social Interaction and Stock-Market Participation," Journal of Finance, American Finance Association, vol. 59(1), pages 137-163, February.
    12. Shive, Sophie, 2010. "An Epidemic Model of Investor Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(1), pages 169-198, February.
    13. Yoshihiro Yura & Hideki Takayasu & Didier Sornette & Misako Takayasu, 2015. "Financial Knudsen number: breakdown of continuous price dynamics and asymmetric buy and sell structures confirmed by high precision order book information," Papers 1508.06024, arXiv.org.
    14. Fuzhong Nian & Yang Yang & Yayong Shi, 2021. "Fractal Propagation And Immunity On Network," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(06), pages 1-12, September.
    15. Li-Xin Wang, 2016. "Modeling Stock Price Dynamics with Fuzzy Opinion Networks," Papers 1602.06213, arXiv.org.
    16. Bjarke Mønsted & Piotr Sapieżyński & Emilio Ferrara & Sune Lehmann, 2017. "Evidence of complex contagion of information in social media: An experiment using Twitter bots," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-12, September.
    17. Parameswaran Gopikrishnan & Martin Meyer & Luis A Nunes Amaral & H Eugene Stanley, 1998. "Inverse Cubic Law for the Probability Distribution of Stock Price Variations," Papers cond-mat/9803374, arXiv.org, revised May 1998.
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