Lessons Learned Using Genetic Programming in a Stock Picking Context
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @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