Evolving a robust trader in a cyclic double auction market

Created by W.Langdon from gp-bibliography.bib Revision:1.7954

@InProceedings{Whigham:2011:GECCO,

• author = "Peter A. Whigham and Rasika Withanawasam",
• title = "Evolving a robust trader in a cyclic double auction market",
• booktitle = "GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation",
• year = "2011",
• 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",
• isbn13 = "978-1-4503-0557-0",
• pages = "1451--1458",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Dublin, Ireland",
• DOI = "doi:10.1145/2001576.2001771",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "A computational model of a double auction market is introduced and extended to allow a controlled cyclic behaviour in the price signal to be developed. Traders are evolved to maximise profit in this market using Grammatical Evolution, and their properties studied for a range of periods and amplitude of the trend in the price signal. The trader grammar allows decision making based on simple trading rules incorporating the concepts of moving-average oscillators and trading range break-out. The results of this investigation demonstrate that traders evolve a short waiting period between decisions, and that there underlying decision logic reflects the scale of the market price frequency. Evidence is presented that suggests evolving a robust profit-making trader, for a range of price frequency changes, requires the training data to have high frequency variation. More generally, to evolve robust solutions for any complex GP problem, a set of local models or an ensemble and state-based approach, is implied by the results.",
• notes = "Also known as \cite{2001771} 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 Peter Alexander Whigham Rasika Withanawasam

Citations