From market games to real-world markets

P. Jefferies, M. L. Hart, P. M. Hui, N. F. Johnson

Research output: Contribution to journalArticlepeer-review

94 Scopus citations

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 effect of different 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 formalism of Bouchaud 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.

Original languageEnglish (US)
Pages (from-to)493-501
Number of pages9
JournalEuropean Physical Journal B
Volume20
Issue number4
DOIs
StatePublished - Apr 2 2001

Keywords

  • 01.30.Cc Conference proceedings
  • 05.45.Tp Time series analysis
  • 05.65.+b Self-organized systems

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

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