Genetic Programming with Memory For Financial Trading

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{EvoBafin16Agapitosetal,

• author = "Alexandros Agapitos and Anthony Brabazon and Michael O'Neill",
• title = "Genetic Programming with Memory For Financial Trading",
• booktitle = "19th European Conference on the Applications of Evolutionary Computation",
• year = "2016",
• editor = "Giovanni Squillero and Paolo Burelli",
• series = "Lecture Notes in Computer Science",
• volume = "9597",
• pages = "19--34",
• address = "Porto, Portugal",
• month = mar # " 30 - " # apr # " 1",
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://dx.doi.org/10.1007/978-3-319-31204-0_2",
• DOI = "doi:10.1007/978-3-319-31204-0_2",
• abstract = "A memory-enabled program representation in strongly-typed Genetic Programming (GP) is compared against the standard representation in a number of financial time-series modelling tasks. The paper first presents a survey of GP systems that use memory. Thereafter, a number of simulations show that memory-enabled programs generalise better than their standard counterparts in most datasets of this problem domain.",
• notes = "EvoApplications2016 held in conjunction with EuroGP'2016, EvoCOP2016 and EvoMusArt2016",

}

Genetic Programming entries for Alexandros Agapitos Anthony Brabazon Michael O'Neill

Citations