IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v48y2016i4d10.1007_s10614-015-9539-y.html
   My bibliography  Save this article

Volatility Analysis of Financial Agent-Based Market Dynamics from Stochastic Contact System

Author

Listed:
  • Di Xiao

    (Beijing Jiaotong Universitly)

  • Jun Wang

    () (Beijing Jiaotong Universitly)

  • Hongli Niu

    (Beijing Jiaotong Universitly)

Abstract

A financial agent-based time series model is developed and investigated by the stochastic contact systems. Multicolor contact system, as one of statistical physics systems, is applied to model a random stock price process for investigating the fluctuation dynamics of financial market. The interaction and dispersal of different types of investment attitudes in a financial market is imitated by viruses spreading in a multicolor contact system, and we suppose that the investment attitudes of market participants contribute to the volatilities of financial time series. We introduce a volatility duration analysis to detect the duration and intensity relationship of time series for both SSECI and the financial model. Furthermore, the empirical research is also presented to study the nonlinear behaviors of returns for the actual data and the simulation data.

Suggested Citation

  • Di Xiao & Jun Wang & Hongli Niu, 2016. "Volatility Analysis of Financial Agent-Based Market Dynamics from Stochastic Contact System," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 607-625, December.
    • Handle: RePEc:kap:compec:v:48:y:2016:i:4:d:10.1007_s10614-015-9539-y
    DOI: 10.1007/s10614-015-9539-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-015-9539-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    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. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
    2. 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.
    3. Divakaran, Uma & Dutta, Amit, 2007. "Long-range connections, quantum magnets and dilute contact processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(1), pages 39-43.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    6. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
    7. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    8. 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.
    9. Kirill Ilinski, 1997. "Physics of Finance," Papers hep-th/9710148, arXiv.org.
    10. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    11. Wang, Tiansong & Wang, Jun & Zhang, Junhuan & Fang, Wen, 2011. "Voter interacting systems applied to Chinese stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2492-2506.
    12. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.),THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    13. Plerou, Vasiliki & Gopikrishnan, Parameswaran & Rosenow, Bernd & Amaral, Luis A.N. & Stanley, H.Eugene, 2000. "Econophysics: financial time series from a statistical physics point of view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 279(1), pages 443-456.
    14. Xiao, Di & Wang, Jun, 2012. "Modeling stock price dynamics by continuum percolation system and relevant complex systems analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4827-4838.
    15. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, 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. Wang, Wentao & Zhang, Junhuan & Zhao, Shangmei & Zhang, Yanglin, 2019. "Simulation of asset pricing in information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 620-634.
    2. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2020. "Fluctuation and volatility dynamics of stochastic interacting energy futures price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Xing, Yani & Wang, Jun, 2019. "Statistical volatility duration and complexity of financial dynamics on Sierpinski gasket lattice percolation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 234-247.
    4. Jia, Linlu & Ke, Jinchuan & Wang, Jun, 2020. "Fluctuation behavior analysis of stochastic exclusion financial dynamics with random jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).

    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:kap:compec:v:48:y:2016:i:4:d:10.1007_s10614-015-9539-y. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.