Adaptive Trading with Grammatical Evolution

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

@InProceedings{dempsey:2006:CEC,

• author = "Ian Dempsey and Michael O'Neill and Anthony Brabazon",
• title = "Adaptive Trading with Grammatical Evolution",
• booktitle = "Proceedings of the 2006 IEEE Congress on Evolutionary Computation",
• year = "2006",
• pages = "9137--9142",
• address = "Vancouver",
• month = "16-21 " # jul,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• ISBN = "0-7803-9487-9",
• DOI = "doi:10.1109/CEC.2006.1688631",
• size = "6 pages",
• abstract = "This study reports on the performance of an on-line evolutionary automatic programming methodology for uncovering technical trading rules for the S&P 500 and Nikkei 225 indices. The system adopts a variable sized investment strategy based on the strength of the signals produced by the trading rules. Two approaches are explored, one using a single population of rules which is adapted over the lifetime of the data and another whereby a new population is created for each step across the time series. The results show profitable performance for the trading periods explored with clear advantages for an adaptive population of rules.",
• notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Ian Dempsey Michael O'Neill Anthony Brabazon

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