An Automated Investing Method for Stock Market Based on Multiobjective Genetic Programming

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@Article{Pimenta:CE,
  author =       "Alexandre Pimenta and Ciniro A. L. Nametala and 
                 Frederico G. Guimaraes and Eduardo G. Carrano",
  title =        "An Automated Investing Method for Stock Market Based
                 on Multiobjective Genetic Programming",
  journal =      "Computational Economics",
  keywords =     "genetic algorithms, genetic programming,
                 Multiobjective optimization, Technical analysis, Stock
                 exchange market, Feature selection, BOVESPA",
  ISSN =         "1572-9974",
  DOI =          "doi:10.1007/s10614-017-9665-9",
  size =         "20 pages",
  abstract =     "Stock market automated investing is an area of strong
                 interest for the academia, casual, and professional
                 investors. In addition to conventional market methods,
                 various sophisticated techniques have been employed to
                 deal with such a problem, such as ARCH/GARCH
                 predictors, artificial neural networks, fuzzy logic,
                 etc. A computational system that combines a
                 conventional market method (technical analysis),
                 genetic programming, and multiobjective optimization is
                 proposed in this work. This system was tested in six
                 historical time series of representative assets from
                 Brazil stock exchange market (BOVESPA). The proposed
                 method led to profits considerably higher than the
                 variation of the assets in the period. The financial
                 return was positive even in situations in which the
                 share lost market value.",
  notes =        "Pimenta's PhD thesis?",
}

Genetic Programming entries for Alexandre Pimenta Ciniro Aparecido Leite Nametala Frederico Gadelha Guimaraes Eduardo Gontijo Carrano

Citations