A mixed-game and co-evolutionary genetic programming agent-based model of financial contagion

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@InProceedings{Liu:2010:cec,
  author =       "Fang Liu and Antoaneta Serguieva and Paresh Date",
  title =        "A mixed-game and co-evolutionary genetic programming
                 agent-based model of financial contagion",
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-6910-9",
  abstract =     "Over the past two decades, financial market crises
                 with similar features have occurred in different
                 regions of the world. Unstable cross-market linkages
                 during financial crises are referred to as financial
                 contagion. We simulate the transmission of financial
                 crises in the context of a model of market participants
                 adopting various strategies; this allows testing for
                 financial contagion under alternative scenarios. Using
                 a comprehensive approach, we develop an agent-based
                 multinational model and investigate the reasons for
                 contagion. Our model comprises four types of traders:
                 noise, herd, game, and technical traders respectively.
                 Different types of traders use different computational
                 strategies to make buy, sell, or hold decisions.
                 Although contagion has been extensively investigated in
                 the financial literature, it has not yet been studied
                 through computational intelligence techniques. Our
                 simulations shed light on parameter values and
                 characteristics which can be exploited to detect
                 contagion at an earlier stage, hence recognising
                 financial crises with the potential to destabilise
                 cross-market linkages. In the real world, such
                 information would be extremely valuable to develop
                 appropriate risk management strategies.",
  DOI =          "doi:10.1109/CEC.2010.5586243",
  notes =        "WCCI 2010. Also known as \cite{5586243}",
}

Genetic Programming entries for Fang Liu Antoaneta Serguieva Paresh Date

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