Evolutionary Induction of Trading Models

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InCollection{bhattacharyya:2002:ECEF,

• author = "Siddhartha Bhattacharyya and Kumar Mehta",
• title = "Evolutionary Induction of Trading Models",
• booktitle = "Evolutionary Computation in Economics and Finance",
• publisher = "Physica Verlag",
• year = "2002",
• editor = "Shu-Heng Chen",
• volume = "100",
• series = "Studies in Fuzziness and Soft Computing",
• chapter = "17",
• pages = "311--332",
• month = "2002",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-7908-1476-8",
• URL = "http://tigger.uic.edu/~sidb/papers/EvolInductionOfTradingModels.pdf",
• DOI = "doi:10.1007/978-3-7908-1784-3_17",
• abstract = "Financial markets data present a challenging opportunity for the learning of complex patterns not readily discernable. This paper investigates the use of genetic algorithms for the mining of financial time-series for patterns aimed at the provision of trading decision models. A simple yet flexible representation for trading rules is proposed, and issues pertaining to fitness evaluation examined. Two key issues in fitness evaluation, the design of a suitable fitness function reflecting desired trading characteristics and choice of appropriate training duration, are discussed and empirically examined. Two basic measures are also proposed for characterising rules obtained with alternate fitness criteria.",
• size = "22 pages",

}

Genetic Programming entries for Siddhartha Bhattacharyya Kumar Mehta

Citations