Combining Technical Analysis and Grammatical Evolution in a Trading System

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Contreras:evoapps13,
  author =       "Ivan Contreras and J. Ignacio Hidalgo and 
                 Laura Nunez-Letamendia",
  title =        "Combining Technical Analysis and Grammatical Evolution
                 in a Trading System",
  booktitle =    "Applications of Evolutionary Computing,
                 EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY,
                 EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR,
                 EvoRISK, EvoROBOT, EvoSTOC",
  year =         "2013",
  month =        "3-5 " # apr,
  editor =       "Anna I. Esparcia-Alcazar and Antonio Della Cioppa and 
                 Ivanoe {De Falco} and Ernesto Tarantino and 
                 Carlos Cotta and Robert Schaefer and Konrad Diwold and 
                 Kyrre Glette and Andrea Tettamanzi and 
                 Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and 
                 Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and 
                 Aniko Ekart and Francisco {Fernandez de Vega} and 
                 Sara Silva and Evert Haasdijk and Gusz Eiben and 
                 Anabela Simoes and Philipp Rohlfshagen",
  series =       "LNCS",
  volume =       "7835",
  publisher =    "Springer Verlag",
  address =      "Vienna",
  publisher_address = "Berlin",
  pages =        "244--253",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution",
  isbn13 =       "978-3-642-37191-2",
  DOI =          "doi:10.1007/978-3-642-37192-9_25",
  size =         "10 pages",
  abstract =     "Trading Systems are beneficial for financial
                 investments due to the complexity of nowadays markets.
                 On one hand, finance markets are influenced by a great
                 amount of factors of different sources such as
                 government policies, natural disasters, international
                 trade, political factors etc. On the other hand,
                 traders, brokers or practitioners in general could be
                 affected by human emotions, so their behaviour in the
                 stock market becomes nonobjective. The high pressure
                 induced by handling a large volume of money is the main
                 reason of the so-called market psychology. Trading
                 systems are able to avoid a great amount of these
                 factors, allowing investors to abstract the complex
                 flow of information and the emotions related to the
                 investments. In this paper we compare two trading
                 systems based on Evolutionary Computation. The first is
                 a GA-based one and was already proposed and tested with
                 data from 2006. The second one is a grammatical
                 evolution approach which uses a new evaluation method.
                 Experimental results show that the later outperforms
                 the GA approach with a set of selected companies of the
                 Spanish market with 2012 data.",
  notes =        "http://www.kevinsim.co.uk/evostar2013/cfpEvoApplications.html
                 EvoApplications2013 held in conjunction with
                 EuroGP2013, EvoCOP2013, EvoBio'2013 and EvoMusArt2013",
}

Genetic Programming entries for Ivan Contreras Jose Ignacio Hidalgo Perez Laura Nunez-Letamendia

Citations