Dynamic Trade Execution: A Grammatical Evolution Approach

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@Article{CuiBO:2011:IJFMDDTEAGEA,
  author =       "Wei Cui and Anthony Brabazon and Michael O'Neill",
  title =        "Dynamic Trade Execution: A Grammatical Evolution
                 Approach",
  journal =      "International Journal of Financial Markets and
                 Derivatives",
  year =         "2011",
  volume =       "2",
  number =       "1-2",
  pages =        "4--31",
  note =         "Special Issue on Computational Methods For Financial
                 Engineering Guest Editors: Dr. Nikolaos S. Thomaidis
                 and Dr. Christos Floros",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, algorithmic trading, trade execution,
                 artificial stock markets, evolutionary computation,
                 financial markets, market impact, opportunity cost,
                 agent-based systems.",
  ISSN =         "1756-7130",
  URL =          "http://www.inderscience.com/info/inarticle.php?artid=38526",
  DOI =          "doi:10.1504/IJFMD.2011.038526",
  abstract =     "Trade execution is concerned with the actual mechanics
                 of buying or selling the desired amount of a financial
                 instrument. Investors wishing to execute large orders
                 face a tradeoff between market impact and opportunity
                 cost. Trade execution strategies are designed to
                 balance out these costs, thereby minimising total
                 trading cost. Despite the importance of optimising the
                 trade execution process, this is difficult to do in
                 practice due to the dynamic nature of markets and due
                 to our imperfect understanding of them. In this paper,
                 we adopt a novel approach, combining an evolutionary
                 methodology whereby we evolve high-quality trade
                 execution strategies, with an agent-based artificial
                 stock market, wherein the evolved strategies are
                 tested. The evolved strategies are found to outperform
                 a series of benchmark strategies and several avenues
                 are suggested for future work.",
  notes =        "http://www.inderscience.com/jhome.php?jcode=ijfmd",
}

Genetic Programming entries for Wei Cui Anthony Brabazon Michael O'Neill

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