IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v299y2001i1p222-227.html
   My bibliography  Save this article

Application of multi-agent games to the prediction of financial time series

Author

Listed:
  • Johnson, Neil F.
  • Lamper, David
  • Jefferies, Paul
  • Hart, Michael L.
  • Howison, Sam

Abstract

We report on a technique based on multi-agent games which has potential use in the prediction of future movements of financial time series. A third-party game is trained on a black-box time series, and is then run into the future to extract next-step and multi-step predictions. In addition to the possibility of identifying profit opportunities, the technique may prove useful in the development of improved risk management strategies.

Suggested Citation

  • Johnson, Neil F. & Lamper, David & Jefferies, Paul & Hart, Michael L. & Howison, Sam, 2001. "Application of multi-agent games to the prediction of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 222-227.
    • Handle: RePEc:eee:phsmap:v:299:y:2001:i:1:p:222-227
    DOI: 10.1016/S0378-4371(01)00299-0
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437101002990
    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(01)00299-0?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. J. Wiesinger & D. Sornette & J. Satinover, 2013. "Reverse Engineering Financial Markets with Majority and Minority Games Using Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 475-492, April.
    2. Zhang, H.S. & Shen, X.Y. & Huang, J.P., 2016. "Pattern of trends in stock markets as revealed by the renormalization method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 340-346.
    3. Li, Da-Ye & Nishimura, Yusaku & Men, Ming, 2014. "Fractal markets: Liquidity and investors on different time horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 144-151.
    4. Guglielmo Maria Caporale & Antoaneta Serguieva & Hao Wu, 2009. "Financial contagion: evolutionary optimization of a multinational agent‐based model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 111-125, January.
    5. Gou, Chengling, 2006. "Deduction of initial strategy distributions of agents in mix-game models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 633-640.
    6. Wei, J.R. & Huang, J.P. & Hui, P.M., 2013. "An agent-based model of stock markets incorporating momentum investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(12), pages 2728-2735.
    7. Zhang, Mengqi & Jiang, Xin & Fang, Zehua & Zeng, Yue & Xu, Ke, 2019. "High-order Hidden Markov Model for trend prediction in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 1-12.
    8. Stefan, F.M. & Atman, A.P.F., 2015. "Is there any connection between the network morphology and the fluctuations of the stock market index?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 630-641.
    9. Groot, Robert D. & Musters, Pieter A.D., 2005. "Minority Game of price promotions in fast moving consumer goods markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 533-547.
    10. Daye Li & Rongrong Li & Qiankun Sun, 2017. "How the heterogeneity in investment horizons affects market trends," Applied Economics, Taylor & Francis Journals, vol. 49(15), pages 1473-1482, March.
    11. Chen, Fang & Gou, Chengling & Guo, Xiaoqian & Gao, Jieping, 2008. "Prediction of stock markets by the evolutionary mix-game model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3594-3604.
    12. Schinckus, C., 2013. "Between complexity of modelling and modelling of complexity: An essay on econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3654-3665.
    13. Derveeuw, Julien, 2005. "Market dynamics and agents behaviors: a computational approach," MPRA Paper 4916, University Library of Munich, Germany.

    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:299:y:2001:i:1:p:222-227. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.