Stock trading using linear genetic programming with multiple time frames
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Wilson:2011:GECCO,
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author = "Garnett Wilson and Derek Leblanc and
Wolfgang Banzhaf",
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title = "Stock trading using linear genetic programming with
multiple time frames",
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booktitle = "GECCO '11: Proceedings of the 13th annual conference
on Genetic and evolutionary computation",
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year = "2011",
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editor = "Natalio Krasnogor and Pier Luca Lanzi and
Andries Engelbrecht and David Pelta and Carlos Gershenson and
Giovanni Squillero and Alex Freitas and
Marylyn Ritchie and Mike Preuss and Christian Gagne and
Yew Soon Ong and Guenther Raidl and Marcus Gallager and
Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and
Nikolaus Hansen and Silja Meyer-Nieberg and
Jim Smith and Gus Eiben and Ester Bernado-Mansilla and
Will Browne and Lee Spector and Tina Yu and Jeff Clune and
Greg Hornby and Man-Leung Wong and Pierre Collet and
Steve Gustafson and Jean-Paul Watson and
Moshe Sipper and Simon Poulding and Gabriela Ochoa and
Marc Schoenauer and Carsten Witt and Anne Auger",
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isbn13 = "978-1-4503-0557-0",
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pages = "1667--1674",
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keywords = "genetic algorithms, genetic programming, Real world
applications",
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month = "12-16 " # jul,
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organisation = "SIGEVO",
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address = "Dublin, Ireland",
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DOI = "doi:10.1145/2001576.2001801",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "A number of researchers have attempted to take
successful GP trading systems and make them even better
through the use of filters. We investigate the use of a
linear genetic programming (LGP) system that combines
GP signals provided over multiple intraday time frames
to produce one trading action. Four combinations of
time frames stretching further into the past are
examined. Two different decision mechanisms for
evaluating the overall signal given the GP signals over
all time frames are also examined, one based on
majority vote and another based on temporal proximity
to the buying decision. Results indicated that majority
vote outperformed emphasis on proximity of time frames
to the current trading decision. Analyses also
indicated that longer time frame combinations were more
conservative and outperformed shorter combinations for
both overall upward and downward price trends.",
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notes = "Also known as \cite{2001801} GECCO-2011 A joint
meeting of the twentieth international conference on
genetic algorithms (ICGA-2011) and the sixteenth annual
genetic programming conference (GP-2011)",
- }
Genetic Programming entries for
Garnett Carl Wilson
Derek Leblanc
Wolfgang Banzhaf
Citations