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From market games to real-world markets

Author

Listed:
  • Paul Jefferies
  • Michael Hart
  • Neil Johnson
  • P.M. Hui

Abstract

This paper uses the development of multi-agent market models to present a unified approach to the joint questions of how financial market movements may be simulated, predicted, and hedged against. We first present the results of agent-based market simulations in which traders equipped with simple buy/sell strategies and limited information compete in speculatory trading. We examine the efect of diferent market clearing mechanisms and show that implementation of a simple Walrasian auction leads to unstable market dynamics. We then show that a more realistic out-of-equilibrium clearing process leads to dynamics that closely resemble real financial movements, with fat-tailed price increments, clustered volatility and high volume autocorrelation. We then show that replacing the `synthetic' price history used by these simulations with data taken from real financial time-series leads to the remarkable result that the agents can collectively learn to identify moments in the market where profit is attainable. Hence on real financial data, the system as a whole can perform better than random. We then employ the risk-control formalism of Bouchaud and Sornette in conjunction with agent based models to show that in general risk cannot be eliminated from trading with these models. We also show that, in the presence of transaction costs, the risk of option writing is greatly increased. This risk, and the costs, can however be reduced through the use of a delta-hedging strategy with modified, time-dependent volatility structure.

Suggested Citation

  • 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.
  • Handle: RePEc:sbs:wpsefe:2001mf02
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    File URL: http://www.finance.ox.ac.uk/file_links/finecon_papers/2001mf02.pdf
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    Cited by:

    1. Zapart, Christopher A., 2009. "On entropy, financial markets and minority games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1157-1172.
    2. 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.
    3. 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.
    4. Matteo Ortisi & Valerio Zuccolo, 2012. "From Minority Game to Black & Scholes pricing," Papers 1205.2521, arXiv.org, revised May 2013.
    5. Wawrzyniak, Karol & Wiƛlicki, Wojciech, 2012. "Mesoscopic approach to minority games in herd regime," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2056-2082.
    6. Ohira, Toru & Sazuka, Naoya & Marumo, Kouhei & Shimizu, Tokiko & Takayasu, Misako & Takayasu, Hideki, 2002. "Predictability of currency market exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 368-374.
    7. Damien Challet & Tobias Galla, 2005. "Price return autocorrelation and predictability in agent-based models of financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 569-576.
    8. Liu, Xinghua & Gregor, Shirley & Yang, Jianmei, 2008. "The effects of behavioral and structural assumptions in artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2535-2546.
    9. 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.
    10. Xin, C. & Yang, G. & Huang, J.P., 2017. "Ising game: Nonequilibrium steady states of resource-allocation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 666-673.
    11. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical regularities of order placement in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3173-3182.
    12. Ren, F. & Zhang, Y.C., 2008. "Trading model with pair pattern strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5523-5534.
    13. Ferreira, Fernando F & Francisco, Gerson & Machado, Birajara S & Muruganandam, Paulsamy, 2003. "Time series analysis for minority game simulations of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 321(3), pages 619-632.

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