IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v287y2000i3p507-523.html
   My bibliography  Save this article

Evolutionary financial market models

Author

Listed:
  • Ponzi, A.
  • Aizawa, Y.

Abstract

We study computer simulations of two financial market models, the second a simplified model of the first. The first is a model of the self-organized formation and breakup of crowds of traders, motivated by the dynamics of competitive evolving systems which shows interesting self-organized critical (SOC)-type behaviour without any fine tuning of control parameters. This SOC-type avalanching and stasis appear as realistic volatility clustering in the price returns time series. The market becomes highly ordered at ‘crashes’ but gradually loses this order through randomization during the intervening stasis periods. The second model is a model of stocks interacting through a competitive evolutionary dynamic in a common stock exchange. This model shows a self-organized ‘market-confidence’. When this is high the market is stable but when it gets low the market may become highly volatile. Volatile bursts rapidly increase the market confidence again. This model shows a phase transition as temperature parameter is varied. The price returns time series in the transition region is very realistic power-law truncated Levy distribution with clustered volatility and volatility superdiffusion. This model also shows generally positive stock cross-correlations as is observed in real markets. This model may shed some light on why such phenomena are observed.

Suggested Citation

  • Ponzi, A. & Aizawa, Y., 2000. "Evolutionary financial market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 507-523.
    • Handle: RePEc:eee:phsmap:v:287:y:2000:i:3:p:507-523
    DOI: 10.1016/S0378-4371(00)00389-7
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437100003897
    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/S0378-4371(00)00389-7?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. Yanhui Liu & Parameswaran Gopikrishnan & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1999. "The statistical properties of the volatility of price fluctuations," Papers cond-mat/9903369, arXiv.org, revised Mar 1999.
    2. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    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. Groot, Robert D., 2005. "Lévy distribution and long correlation times in supermarket sales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 501-514.
    2. Salvador Pueyo, 2014. "Ecological Econophysics for Degrowth," Sustainability, MDPI, vol. 6(6), pages 1-53, May.
    3. Beyeler, Walter E. & Glass, Robert J. & Bech, Morten L. & Soramäki, Kimmo, 2007. "Congestion and cascades in payment systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 693-718.
    4. Wu, Jinshan & Di, Zengru & Yang, Zhanru, 2003. "Division of labor as the result of phase transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 663-676.
    5. R. D. Groot, 2004. "Levy distribution and long correlation times in supermarket sales," Papers cond-mat/0412163, arXiv.org.
    6. Sun-Chong Wang & Sai-Ping Li & Chung-Ching Tai & Shu-Heng Che, 2009. "Statistical properties of an experimental political futures market," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 9-16.
    7. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.

    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. Muchnik, Lev & Bunde, Armin & Havlin, Shlomo, 2009. "Long term memory in extreme returns of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4145-4150.
    2. Zhang, Jiu & Jin, Li-Fu & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2022. "Simplified calculations of time correlation functions in non-stationary complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    3. Dusan Stosic & Darko Stosic & Tatijana Stosic, 2019. "Nonextensive triplets in stock market indices," Papers 1901.07721, arXiv.org.
    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. Stanley, H.Eugene, 2000. "Exotic statistical physics: Applications to biology, medicine, and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 1-17.
    6. Stosic, Dusan & Stosic, Darko & Stosic, Tatijana, 2019. "Nonextensive triplets in stock market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 192-198.
    7. Ouyang, Fang-Yan & Zheng, Bo & Jiang, Xiong-Fei, 2019. "Dynamic fluctuations of cross-correlations in multi-time scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 515-521.
    8. Mao, Xuegeng & Shang, Pengjian, 2018. "Extended AIC model based on high order moments and its application in the financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 264-275.
    9. Stanislav S Borysov & Alexander V Balatsky, 2014. "Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-11, August.
    10. Jun-Jie Chen & Lei Tan & Bo Zheng, 2015. "Agent-based model with multi-level herding for complex financial systems," Papers 1504.01811, arXiv.org.
    11. Fang-Yan Ouyang & Bo Zheng & Xiong-Fei Jiang, 2015. "Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-18, October.
    12. Paul Ormerod, 2010. "La crisis actual y la culpabilidad de la teoría macroeconómica," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 12(22), pages 111-128, January-J.
    13. Hu, Kun & Ivanov, Plamen Ch. & Chen, Zhi & Hilton, Michael F. & Stanley, H.Eugene & Shea, Steven A., 2004. "Non-random fluctuations and multi-scale dynamics regulation of human activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 307-318.
    14. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    15. Tobias Wand & Oliver Kamps & Hiroshi Iyetomi, 2024. "Causal Hierarchy in the Financial Market Network -- Uncovered by the Helmholtz-Hodge-Kodaira Decomposition," Papers 2408.12839, arXiv.org.
    16. Andrés García-Medina & Graciela González Farías, 2020. "Transfer entropy as a variable selection methodology of cryptocurrencies in the framework of a high dimensional predictive model," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-31, January.
    17. Tobias Wand & Martin He{ss}ler & Oliver Kamps, 2022. "Identifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data," Papers 2208.14106, arXiv.org, revised Mar 2023.
    18. Antti J. Tanskanen & Jani Lukkarinen & Kari Vatanen, 2016. "Random selection of factors preserves the correlation structure in a linear factor model to a high degree," Papers 1604.05896, arXiv.org, revised Dec 2018.
    19. Pafka, Szilárd & Kondor, Imre, 2001. "Evaluating the RiskMetrics methodology in measuring volatility and Value-at-Risk in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 305-310.
    20. Maria Letizia Bertotti & Amit K Chattopadhyay & Giovanni Modanese, 2017. "Economic inequality and mobility for stochastic models with multiplicative noise," Papers 1702.08391, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    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:287:y:2000:i:3:p:507-523. 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.