Co-Evolving Trading Strategies to Analyze Bounded Rationality in Double Auction Markets

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{Chen:2008:GPTP,
  author =       "Shu-Heng Chen and Ren-Jie Zeng and Tina Yu",
  title =        "Co-Evolving Trading Strategies to Analyze Bounded
                 Rationality in Double Auction Markets",
  booktitle =    "Genetic Programming Theory and Practice {VI}",
  year =         "2008",
  editor =       "Rick L. Riolo and Terence Soule and Bill Worzel",
  series =       "Genetic and Evolutionary Computation",
  chapter =      "13",
  pages =        "195--215",
  address =      "Ann Arbor",
  month =        "15-17 " # may,
  publisher =    "Springer",
  URL =          "http://www.cs.mun.ca/~tinayu/Publications_files/gptp2008.pdf",
  DOI =          "doi:10.1007/978-0-387-87623-8_13",
  size =         "20 pages",
  isbn13 =       "978-0-387-87622-1",
  notes =        "part of \cite{Riolo:2008:GPTP} published in 2009",
  keywords =     "genetic algorithms, genetic programming, bounded
                 rationality, zero-intelligence, agent-based modelling,
                 human subject experiments, auction markets design,
                 double-auction markets, macroeconomics, trading
                 strategies, software agents, market simulation, market
                 efficiency",
  size =         "19 pages",
  abstract =     "We investigate double-auction (DA) market behaviour
                 under traders with different degrees of rationality
                 (intelligence or cognitive ability). The rationality of
                 decision making is implemented using genetic
                 programming (GP), where each trader evolves a
                 population of strategies to conduct an auction. By
                 assigning the GP traders different population sizes to
                 differentiate their cognitive ability, through a series
                 of simulations, we find that increasing the traders
                 intelligence improves the markets efficiency. However,
                 increasing the number of intelligent traders in the
                 market leads to a decline in the markets efficiency. By
                 analysing the individual GP traders strategies and
                 their co-evolution dynamics, we provide explanations to
                 these emerging market phenomena. While auction markets
                 are gaining popularity on the Internet, the insights
                 can help market designers devise robust and efficient
                 auction e-markets.",
}

Genetic Programming entries for Shu-Heng Chen Ren-Jie Zeng Tina Yu

Citations