Application of Genetic Algorithms in Stock Market Simulation

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Stepanek:2012:PSBS,
  author =       "Jiri Stepanek and Jiri Stovicek and Richard Cimler",
  title =        "Application of Genetic Algorithms in Stock Market
                 Simulation",
  journal =      "Procedia - Social and Behavioral Sciences",
  volume =       "47",
  pages =        "93--97",
  year =         "2012",
  note =         "Cyprus International Conference on Educational
                 Research (CY-ICER-2012) North Cyprus, US08-10 February,
                 2012",
  keywords =     "genetic algorithms, genetic programming, evolution
                 algorithms, multiagent simulation, stock-market",
  ISSN =         "1877-0428",
  DOI =          "doi:10.1016/j.sbspro.2012.06.619",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1877042812023555",
  abstract =     "Development of stock market is affected by many
                 factors. It is difficult to predict changes in prices
                 of stocks because of many parameters in behavioural
                 algorithms. There is also problem with learning
                 soft-skills because of many variables. Application of
                 genetic algorithms can help find suitable pre-set of
                 behavioural patterns, functions and its parameters. In
                 this paper we describe creation and implementation
                 genetic algorithms to existing multi-agent simulation.
                 This existing simulation provides basic model of
                 simulation of stock market members behaviour. The main
                 goal of this article is describe how to implement
                 genetic algorithm into this type of simulation. The
                 main advantage of using genetic algorithms is
                 dynamically created decision process or function of
                 each agent. Article describes process of creating
                 decision, simulating behaviour of agents which decision
                 algorithm was created by genetic programming. Next
                 point is to show, how can be this implementation of
                 genetic algorithms used in learning process of
                 simulation.",
}

Genetic Programming entries for Jiri Stepanek Jiri Stovicek Richard Cimler

Citations