IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v432y2015icp301-314.html
   My bibliography  Save this article

Volatility behavior of visibility graph EMD financial time series from Ising interacting system

Author

Listed:
  • Zhang, Bo
  • Wang, Jun
  • Fang, Wen

Abstract

A financial market dynamics model is developed and investigated by stochastic Ising system, where the Ising model is the most popular ferromagnetic model in statistical physics systems. Applying two graph based analysis and multiscale entropy method, we investigate and compare the statistical volatility behavior of return time series and the corresponding IMF series derived from the empirical mode decomposition (EMD) method. And the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, we find that the degree distribution of visibility graph for the simulation series has the power law tails, and the assortative network exhibits the mixing pattern property. All these features are in agreement with the real market data, the research confirms that the financial model established by the Ising system is reasonable.

Suggested Citation

  • Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
  • Handle: RePEc:eee:phsmap:v:432:y:2015:i:c:p:301-314
    DOI: 10.1016/j.physa.2015.03.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115003192
    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.2015.03.057?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. Bentes, Sónia R., 2015. "A comparative analysis of the predictive power of implied volatility indices and GARCH forecasted volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 105-112.
    2. Fulvio Corsi & Stefan Mittnik & Christian Pigorsch & Uta Pigorsch, 2008. "The Volatility of Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 46-78.
    3. Telesca, Luciano & Lovallo, Michele & Ramirez-Rojas, Alejandro & Flores-Marquez, Leticia, 2013. "Investigating the time dynamics of seismicity by using the visibility graph approach: Application to seismicity of Mexican subduction zone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6571-6577.
    4. Qian, Xi-Yuan & Gu, Gao-Feng & Zhou, Wei-Xing, 2011. "Modified detrended fluctuation analysis based on empirical mode decomposition for the characterization of anti-persistent processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4388-4395.
    5. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    6. 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.
    7. Telesca, Luciano & Lovallo, Michele & Pierini, Jorge O., 2012. "Visibility graph approach to the analysis of ocean tidal records," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1086-1091.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Junhuan Zhang & Jun Wang & Jiguang Shao, 2010. "Finite-Range Contact Process On The Market Return Intervals Distributions," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(05), pages 643-657.
    10. Hongli Niu & Jun Wang, 2014. "Phase and multifractality analyses of random price time series by finite-range interacting biased voter system," Computational Statistics, Springer, vol. 29(5), pages 1045-1063, October.
    11. Pierini, Jorge O. & Lovallo, Michele & Telesca, Luciano, 2012. "Visibility graph analysis of wind speed records measured in central Argentina," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5041-5048.
    12. Wang, Jun, 2009. "The estimates of correlations in two-dimensional Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 565-573.
    13. Babikir, Ali & Gupta, Rangan & Mwabutwa, Chance & Owusu-Sekyere, Emmanuel, 2012. "Structural breaks and GARCH models of stock return volatility: The case of South Africa," Economic Modelling, Elsevier, vol. 29(6), pages 2435-2443.
    14. Grau-Carles, Pilar, 2001. "Long-range power-law correlations in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 521-527.
    15. Yao Yu & Jun Wang, 2012. "Lattice-oriented percolation system applied to volatility behavior of stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(4), pages 785-797, August.
    16. Thuraisingham, Ranjit A. & Gottwald, Georg A., 2006. "On multiscale entropy analysis for physiological data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 323-332.
    17. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    18. 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.
    19. Wen Fang & Jun Wang, 2012. "Statistical Properties And Multifractal Behaviors Of Market Returns By Ising Dynamic Systems," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 23(03), pages 1-14.
    20. Kirill Ilinski, 1997. "Physics of Finance," Papers hep-th/9710148, arXiv.org.
    21. 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.
    22. Fang, Wen & Wang, Jun, 2013. "Fluctuation behaviors of financial time series by a stochastic Ising system on a Sierpinski carpet lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4055-4063.
    23. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
    24. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169.
    25. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    26. A. Krawiecki, 2005. "Microscopic Spin Model For The Stock Market With Attractor Bubbling And Heterogeneous Agents," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 549-559.
    27. Costa, M. & Peng, C.-K. & L. Goldberger, Ary & Hausdorff, Jeffrey M., 2003. "Multiscale entropy analysis of human gait dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 53-60.
    28. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2003. "A theory of power-law distributions in financial market fluctuations," Nature, Nature, vol. 423(6937), pages 267-270, May.
    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. Christoph J. Borner & Ingo Hoffmann & John H. Stiebel, 2024. "A closer look at the chemical potential of an ideal agent system," Papers 2401.09233, arXiv.org.
    2. Wang, Haoyu & Di, Junpeng & Yang, Zhaojun & Han, Qing, 2020. "Assessment of mutual fund performance based on Ensemble Empirical Mode Decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    3. 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.
    4. Luo, Changqing & Liu, Lan & Wang, Da, 2021. "Multiscale financial risk contagion between international stock markets: Evidence from EMD-Copula-CoVaR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Zhang, Ditian & Zhuang, Yangyang & Tang, Pan & Han, Qingying, 2022. "The evolution of foreign exchange market: A network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).
    6. Ditian Zhang & Yangyang Zhuang & Pan Tang & Hongjuan Peng & Qingying Han, 2023. "Financial price dynamics and phase transitions in the stock markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(3), pages 1-21, March.
    7. Braga, A.C. & Alves, L.G.A. & Costa, L.S. & Ribeiro, A.A. & de Jesus, M.M.A. & Tateishi, A.A. & Ribeiro, H.V., 2016. "Characterization of river flow fluctuations via horizontal visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 1003-1011.
    8. Sun, Mei & Wang, Yaqi & Gao, Cuixia, 2016. "Visibility graph network analysis of natural gas price: The case of North American market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1-11.

    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. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    2. B. Zhang & J. Wang & W. Zhang & G. C. Wang, 2020. "Nonlinear Scaling Behavior of Visible Volatility Duration for Financial Statistical Physics Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 373-389, August.
    3. 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.
    4. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    5. 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.
    6. Zeng, Yayun & Wang, Jun & Xu, Kaixuan, 2017. "Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 364-376.
    7. Zhang, Wei & Wang, Jun, 2017. "Nonlinear stochastic exclusion financial dynamics modeling and time-dependent intrinsic detrended cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 29-41.
    8. 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.
    9. Hongli Niu & Jun Wang, 2014. "Phase and multifractality analyses of random price time series by finite-range interacting biased voter system," Computational Statistics, Springer, vol. 29(5), pages 1045-1063, October.
    10. Niu, Hongli & Wang, Jun, 2013. "Complex dynamic behaviors of oriented percolation-based financial time series and Hang Seng index," Chaos, Solitons & Fractals, Elsevier, vol. 52(C), pages 36-44.
    11. Niu, Hongli & Wang, Jun, 2017. "Return volatility duration analysis of NYMEX energy futures and spot," Energy, Elsevier, vol. 140(P1), pages 837-849.
    12. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    13. 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.
    14. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    15. 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).
    16. Wang, Jie & Wang, Jun, 2020. "Cross-correlation complexity and synchronization of the financial time series on Potts dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    17. Niu, Hongli & Wang, Jun & Lu, Yunfan, 2016. "Fluctuation behaviors of financial return volatility duration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 30-40.
    18. Giacomo Bormetti & Sofia Cazzaniga, 2014. "Multiplicative noise, fast convolution and pricing," Quantitative Finance, Taylor & Francis Journals, vol. 14(3), pages 481-494, March.
    19. Wang, Yiduan & Zheng, Shenzhou & Zhang, Wei & Wang, Jun & Wang, Guochao, 2018. "Modeling and complexity of stochastic interacting Lévy type financial price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 498-511.
    20. Ko, Bonggyun & Kim, Kyungwon, 2017. "Simulation of sovereign CDS market based on interaction between market participant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 324-340.

    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:432:y:2015:i:c:p:301-314. 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.