Generating Directional Change Based Trading Strategies with Genetic Programming

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

@InProceedings{Gypteau:2015:evoApplications,
  author =       "Jeremie Gypteau and Fernando Otero and 
                 Michael Kampouridis",
  title =        "Generating Directional Change Based Trading Strategies
                 with Genetic Programming",
  booktitle =    "18th European Conference on the Applications of
                 Evolutionary Computation",
  year =         "2015",
  editor =       "Antonio M. Mora and Giovanni Squillero",
  series =       "LNCS",
  volume =       "9028",
  publisher =    "Springer",
  pages =        "267--278",
  address =      "Copenhagen",
  month =        "8-10 " # apr,
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, Directional
                 changes, Financial forecasting, Trading",
  isbn13 =       "978-3-319-16548-6",
  DOI =          "doi:10.1007/978-3-319-16549-3_22",
  abstract =     "The majority of forecasting tools use a physical time
                 scale for studying price fluctuations of financial
                 markets, making the flow of physical time
                 discontinuous. Therefore, using a physical time scale
                 may expose companies to risks, due to ignorance of some
                 significant activities. In this paper, an alternative
                 and novel approach is explored to capture important
                 activities in the market. The main idea is to use an
                 intrinsic time scale based on Directional Changes.
                 Combined with Genetic Programming, the proposed
                 approach aims to find an optimal trading strategy to
                 forecast the future price moves of a financial market.
                 In order to evaluate its efficiency and robustness as
                 forecasting tool, a series of experiments was
                 performed, where we were able to obtain valuable
                 information about the forecasting performance. The
                 results from the experiments indicate that this new
                 framework is able to generate new and profitable
                 trading strategies.",
  notes =        "EvoFIN EvoApplications2015 held in conjunction with
                 EuroGP'2015, EvoCOP2015 and EvoMusArt2015
                 http://www.evostar.org/2015/cfp_evoapps.php",
}

Genetic Programming entries for Jeremie Gypteau Fernando Esteban Barril Otero Michael Kampouridis

Citations