Discovering Financial Technical Trading Rules Using Genetic Programming with Lambda Abstraction

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

@InCollection{yu:2004:GPTP,
  author =       "Tina Yu and Shu-Heng Chen and Tzu-Wen Kuo",
  title =        "Discovering Financial Technical Trading Rules Using
                 Genetic Programming with Lambda Abstraction",
  booktitle =    "Genetic Programming Theory and Practice {II}",
  year =         "2004",
  editor =       "Una-May O'Reilly and Tina Yu and Rick L. Riolo and 
                 Bill Worzel",
  chapter =      "2",
  pages =        "11--30",
  address =      "Ann Arbor",
  month =        "13-15 " # may,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, modular
                 genetic programming, lambda abstraction modules,
                 higher-order functions, financial trading rules,
                 buy-and-hold, S&P 500 index, automatically defined
                 functions, ADF, PolyGP system, stock market, technical
                 analysis, constrained syntactic structure, strongly
                 typed genetic programming, STGP, financial time series,
                 lambda abstraction GP",
  ISBN =         "0-387-23253-2",
  URL =          "http://www.cs.mun.ca/~tinayu/Publications_files/gptp2004.pdf",
  DOI =          "doi:10.1007/0-387-23254-0_2",
  size =         "20 pages",
  abstract =     "We applied genetic programming with a lambda
                 abstraction module mechanism to learn technical trading
                 rules based on S&P 500 index from 1982 to 2002. The
                 results show strong evidence of excess returns over
                 buy-and-hold after transaction cost. The discovered
                 trading rules can be interpreted easily; each rule uses
                 a combination of one to four widely used technical
                 indicators to make trading decisions. The consensus
                 among these trading rules is high. For the majority of
                 the testing period, 80percent of the trading rules give
                 the same decision. These rules also give high
                 transaction frequency. Regardless of the stock market
                 climate, they are able to identify opportunities to
                 make profitable trades and out-perform buy-and-hold.",
  notes =        "part of \cite{oreilly:2004:GPTP2}

                 ",
}

Genetic Programming entries for Tina Yu Shu-Heng Chen Tzu-Wen Kuo

Citations