On artificial adaptive agents models of stock markets

Hakman A. WAN, Andrew HUNTER

Research output: Journal PublicationsJournal Article (refereed)peer-review

11 Citations (Scopus)


The complex behavior of share prices in a stock market is studied under a modeling technique of artificial adaptive agents. Individual agents who are active in the market are identified and represented by mathematical functions. Share price is then determined by an arithmetic sum of these functions. Iterations of the models produce a time series of share prices, which exhibits nonlinearities similar to those found in real-world stock markets. Several experiments are reported in this paper. The wealth held by an agent at the beginning of the experiment and the method by which the agent adapts himself to market trends are shown to be important to the success of the agent.
Original languageEnglish
Pages (from-to)279-289
Number of pages11
Issue number5
Publication statusPublished - 1 May 1997


  • Artificial adaptive agents
  • deterministic chaos
  • linear regression
  • stock market

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