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Prediction of stock markets by the evolutionary mix-game model

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  • Chen, Fang
  • Gou, Chengling
  • Guo, Xiaoqian
  • Gao, Jieping
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    Abstract

    This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

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    File URL: http://www.sciencedirect.com/science/article/pii/S037843710800188X
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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 387 (2008)
    Issue (Month): 14 ()
    Pages: 3594-3604

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    Handle: RePEc:eee:phsmap:v:387:y:2008:i:14:p:3594-3604

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Forecasting of stock markets; Mix-game model; Evolutionary mix-game model; Adaptability;

    References

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    1. Challet, D. & Zhang, Y.-C., 1997. "Emergence of cooperation and organization in an evolutionary game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 407-418.
    2. N. F. Johnson & D. Lamper & P. Jefferies & M. L. Hart & S. Howison, 2001. "Application of multi-agent games to the prediction of financial time-series," Papers cond-mat/0105303, arXiv.org.
    3. Neil F. Johnson & David Lamper & Paul Jefferies & Michael L. Hart & Sam Howison, 2001. "Application of multi-agent games to the prediction of financial time-series," OFRC Working Papers Series 2001mf04, Oxford Financial Research Centre.
    4. Zhou, Wei-Xing & Sornette, Didier, 2004. "Antibubble and prediction of China's stock market and real-estate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 243-268.
    5. Paul Jefferies & Michael Hart & Neil Johnson & P.M. Hui, 2001. "From market games to real-world markets," OFRC Working Papers Series 2001mf02, Oxford Financial Research Centre.
    6. Challet, Damien & Zhang, Yi-Cheng, 1998. "On the minority game: Analytical and numerical studies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 256(3), pages 514-532.
    7. Marsili, Matteo, 2001. "Market mechanism and expectations in minority and majority games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 93-103.
    8. 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.
    9. 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.
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    Cited by:
    1. Guglielmo Maria Caporale & Antoaneta Serguieva & Hao Wu, 2008. "Financial Contagion: Evolutionary Optimisation of a Multinational Agent-Based Model," CESifo Working Paper Series 2444, CESifo Group Munich.
    2. Karol Wawrzyniak & Wojciech Wi\'slicki, 2013. "Grand canonical minority game as a sign predictor," Papers 1309.3399, arXiv.org.
    3. J. Wiesinger & D. Sornette & J. Satinover, 2013. "Reverse Engineering Financial Markets with Majority and Minority Games Using Genetic Algorithms," Computational Economics, Society for Computational Economics, vol. 41(4), pages 475-492, April.

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