Lessons Learned Using Genetic Programming in a Stock Picking Context

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

@InCollection{caplan:2004:GPTP,

• author = "Michael Caplan and Ying Becker",
• title = "Lessons Learned Using Genetic Programming in a Stock Picking Context",
• booktitle = "Genetic Programming Theory and Practice {II}",
• year = "2004",
• editor = "Una-May O'Reilly and Tina Yu and Rick L. Riolo and Bill Worzel",
• chapter = "6",
• pages = "87--102",
• address = "Ann Arbor",
• month = "13-15 " # may,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, stock selection, data mining, fitness functions, quantitative portfolio management",
• ISBN = "0-387-23253-2",
• DOI = "doi:10.1007/0-387-23254-0_6",
• abstract = "This is a narrative describing the implementation of a genetic programming technique for stock picking in a quantitatively driven, risk-controlled, US equity portfolio. It describes, in general, the problems that the authors faced in their portfolio context when using genetic programming techniques and in gaining acceptance of the technique by a skeptical audience. We discuss in some detail the construction of the fitness function, the genetic programming system's parametrisation (including data selection and internal function choice), and the interpretation and modification of the generated programs for eventual implementation.",
• notes = "part of \cite{oreilly:2004:GPTP2}",

}

Genetic Programming entries for Michael Caplan Ying L Becker

Citations