IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v391y2012i12p3513-3525.html
   My bibliography  Save this article

The endogenous dynamics of financial markets: Interaction and information dissemination

Author

Listed:
  • Yang, ChunXia
  • Hu, Sen
  • Xia, BingYing

Abstract

We investigate the process that different interactions between investors will prompt information to propagate along a differentiated path and construct a financial market model. As information spreads, increasingly investors are attracted to participate in trading, then the “herding effect” is magnified gradually, which will induce the topology of market network to change and the price to fluctuate. Especially, under different initial conditions or parameters, the peak and fat-tail property is produced and the obtained statistic values coincide with empirical results: the power-law exponents between the peak value of return probability distribution and the time scales range from 0.579 to 0.747, and the exponents between the accumulation distribution and the return on the tail are close to 3. Besides, the extent of volatility clustering in our produced price series is close to that of S&P 500 and locates between NASDAQ and HSI. All the results obtained here indicate that the continuous variation of the “herding effect” resulting from information propagation among interacting investors may be the origin of stylized facts of price fluctuations.

Suggested Citation

  • Yang, ChunXia & Hu, Sen & Xia, BingYing, 2012. "The endogenous dynamics of financial markets: Interaction and information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3513-3525.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:12:p:3513-3525
    DOI: 10.1016/j.physa.2012.02.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437112001197
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2012.02.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jie-Jun Tseng & Sai-Ping Li, 2010. "Asset returns and volatility clustering in financial time series," Papers 1002.0284, arXiv.org, revised Apr 2011.
    2. Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
    3. 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.
    4. Stanley, H.E & Amaral, L.A.N & Gopikrishnan, P & Plerou, V, 2000. "Scale invariance and universality of economic fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(1), pages 31-41.
    5. D. Sornette, 2003. "Critical Market Crashes," Papers cond-mat/0301543, arXiv.org.
    6. Tseng, Jie-Jun & Li, Sai-Ping, 2011. "Asset returns and volatility clustering in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1300-1314.
    7. 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.
    8. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    9. Makowiec, D. & Gnaciński, P. & Miklaszewski, W., 2004. "Amplified imitation in percolation model of stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(1), pages 269-278.
    10. Lillo Fabrizio & Farmer J. Doyne, 2004. "The Long Memory of the Efficient Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(3), pages 1-35, September.
    11. Gopikrishnan, P & Plerou, V & Liu, Y & Amaral, L.A.N & Gabaix, X & Stanley, H.E, 2000. "Scaling and correlation in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 362-373.
    12. Gérard Weisbuch & Sorin Solomon, 2000. "Self-Organized Percolation And Critical Sales Fluctuations," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1263-1272.
    13. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    14. B.H. Wang & P.M. Hui, 2001. "The distribution and scaling of fluctuations for Hang Seng index in Hong Kong stock market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 573-579, April.
    15. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    16. Gudrun Ehrenstein, 2002. "Cont-Bouchaud percolation model including Tobin tax," Papers cond-mat/0205320, arXiv.org.
    17. Chen, Shu-Heng & Huang, Ya-Chi, 2008. "Risk preference, forecasting accuracy and survival dynamics: Simulations based on a multi-asset agent-based artificial stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 702-717, September.
    18. Jiang, J. & Ma, K. & Cai, X., 2007. "Non-linear characteristics and long-range correlations in Asian stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 399-407.
    19. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    20. Liu, Xinghua & Liang, Xiaobei & Tang, Bingyong, 2004. "Minority game and anomalies in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 343-352.
    21. Skjeltorp, Johannes A, 2000. "Scaling in the Norwegian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 486-528.
    22. Cai, Shi-Min & Zhou, Pei-Ling & Yang, Hui-Jie & Yang, Chun-Xia & Wang, Bing-Hong & Zhou, Tao, 2006. "Diffusion entropy analysis on the scaling behavior of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 337-344.
    23. Oliver Hein & Michael Schwind & Markus Spiwoks, 2008. "Frankfurt Artificial Stock Market: a microscopic stock market model with heterogeneous interacting agents in small-world communication networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 59-71, June.
    24. Chang, Iksoo & Stauffer, Dietrich, 1999. "Fundamental judgement in Cont–Bouchaud Herding model of market fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 264(1), pages 294-298.
    25. Stauffer, D. & Jan, N., 2000. "Sharp peaks in the percolation model for stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 277(1), pages 215-219.
    26. 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.
    27. Gao-Feng Gu & Wei-Xing Zhou, 2008. "Emergence of long memory in stock volatility from a modified Mike-Farmer model," Papers 0807.4639, arXiv.org, revised May 2009.
    28. 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.
    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. Sen, Hu & Chunxia, Yang & Xueshuai, Zhu & Zhilai, Zheng & Ya, Cao, 2015. "Distributions of region size and GDP and their relation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 46-56.

    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. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    2. T. T. Chen & B. Zheng & Y. Li & X. F. Jiang, 2017. "New approaches in agent-based modeling of complex financial systems," Papers 1703.06840, arXiv.org.
    3. Gao-Feng Gu & Xiong Xiong & Hai-Chuan Xu & Wei Zhang & Yongjie Zhang & Wei Chen & Wei-Xing Zhou, 2021. "An empirical behavioral order-driven model with price limit rules," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    4. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    5. Frank McGroarty & Ash Booth & Enrico Gerding & V. L. Raju Chinthalapati, 2019. "High frequency trading strategies, market fragility and price spikes: an agent based model perspective," Annals of Operations Research, Springer, vol. 282(1), pages 217-244, November.
    6. Roberto Mota Navarro & Hernán Larralde, 2017. "A detailed heterogeneous agent model for a single asset financial market with trading via an order book," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-27, February.
    7. Derksen, M. & Kleijn, B. & de Vilder, R., 2022. "Heavy tailed distributions in closing auctions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    8. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    9. Fang, Wen & Ke, Jinchuan & Wang, Jun & Feng, Ling, 2016. "Linking market interaction intensity of 3D Ising type financial model with market volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 531-542.
    10. M. Derksen & B. Kleijn & R. de Vilder, 2020. "Heavy tailed distributions in closing auctions," Papers 2012.10145, arXiv.org.
    11. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    12. Wei-Xing Zhou, 2012. "Universal price impact functions of individual trades in an order-driven market," Quantitative Finance, Taylor & Francis Journals, vol. 12(8), pages 1253-1263, June.
    13. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    14. Xiaotao Zhang & Jing Ping & Tao Zhu & Yuelei Li & Xiong Xiong, 2016. "Are Price Limits Effective? An Examination of an Artificial Stock Market," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-21, August.
    15. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    16. Leal, Sandrine Jacob & Napoletano, Mauro, 2019. "Market stability vs. market resilience: Regulatory policies experiments in an agent-based model with low- and high-frequency trading," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 15-41.
    17. repec:hal:spmain:info:hdl:2441/6ummnc8nko827b2luohnctekk7 is not listed on IDEAS
    18. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    19. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: I. Empirical facts," Post-Print hal-00621058, HAL.
    20. repec:hal:spmain:info:hdl:2441/3utlh0ehcn860pus6p2p683ade is not listed on IDEAS
    21. Zhang, Yali & Wang, Jun, 2017. "Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 741-756.
    22. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.

    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:eee:phsmap:v:391:y:2012:i:12:p:3513-3525. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.