Prediction of Interday Stock Prices using Developmental and Linear Genetic Programming

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@InProceedings{Wilson:evows09,

• author = "Garnett Wilson and Wolfgang Banzhaf",
• title = "Prediction of Interday Stock Prices using Developmental and Linear Genetic Programming",
• booktitle = "Applications of Evolutionary Computing, EvoWorkshops2009: {EvoCOMNET}, {EvoENVIRONMENT}, {EvoFIN}, {EvoGAMES}, {EvoHOT}, {EvoIASP}, {EvoINTERACTION}, {EvoMUSART}, {EvoNUM}, {EvoPhD}, {EvoSTOC}, {EvoTRANSLOG}",
• year = "2009",
• month = "15-17 " # apr,
• editor = "Mario Giacobini and Ivanoe {De Falco} and Marc Ebner",
• series = "LNCS",
• volume = "5484",
• publisher = "Springer Verlag",
• address = "Tubingen, Germany",
• pages = "172--181",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-01128-3",
• DOI = "doi:10.1007/978-3-642-01129-0_21",
• abstract = "A developmental co-evolutionary genetic programming approach (PAM DGP) is compared to a standard linear genetic programming (LGP) implementation for trading of stocks across market sectors. Both implementations were found to be impressively robust to market fluctuations while reacting efficiently to opportunities for profit, where PAM DGP proved slightly more reactive to market changes than LGP. PAM DGP outperformed, or was competitive with, LGP for all stocks tested. Both implementations had very impressive accuracy in choosing both profitable buy trades and sells that prevented losses, where this occurred in the context of moderately active trading for all stocks. The algorithms also appropriately maintained maximal investment in order to profit from sustained market upswings.",
• notes = "EvoWorkshops2009",

}

Genetic Programming entries for Garnett Carl Wilson Wolfgang Banzhaf

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