Genetic Programming Software to Forecast Time Series

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{RePEc:sce:scecf3:97,
  author =       "M. A. Kaboudan",
  title =        "Genetic Programming Software to Forecast Time Series",
  booktitle =    "Computing in Economics and Finance",
  year =         "2003",
  address =      "University of Washington, Seattle, USA",
  month =        "11-13 " # jul,
  organisation = "Society for Computational Economics",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://bulldog2.redlands.edu/fac/mak_kaboudan/cef2003/Kaboudan_Extended_Abstract_2.pdf",
  abstract =     "Genetic programming (GP) is an optimisation technique
                 useful in forecasting. GP software is available freely
                 on the Internet or can be purchased commercially. Free
                 software demands advanced programming skills, while
                 commercial software may be expensive. This paper
                 introduces TSGP software developed to forecast time
                 series. It is free to download with instructions, works
                 in windows environment, is user-friendly, does not
                 require programming skills, delivers comprehensible
                 output, and reports statistics a time series analyst,
                 statistician, or econometrician finds desirable. This
                 introduction benefits forecasting researchers and
                 practitioners. Genetic programming (GP) emerged in the
                 late 1980s and early 1990s. Koza was first to introduce
                 a formal description of the technique. GP applies to
                 many optimisation areas including modelling time
                 series. Unlike other modelling techniques, GP is a
                 computerised search for specifications that replicate
                 patterns of observed series. Users of GP software
                 provide input files containing mathematical operators
                 and values of variables. The program is designed to
                 randomly assemble specifications of equations until it
                 finds the best one. That equation, its fitted values,
                 residuals, and evaluation statistics are written to
                 output files. Such automated search for specifications
                 makes GP an attractive algorithm. TSGP stands for time
                 series genetic programming. The software is available
                 at HYPERLINK {"}http://www.compumetrica.com{"}
                 www.compumetrica.com.

                 It is an expansion of a code in Koza's 1990 GP book
                 written in LISP that was converted to C by Andy
                 Singleton in 1994. TSGP gets its instructions from a
                 configuration file containing self-reproduction,
                 crossover, and mutation rates, names of input
                 variables, population size, number of generations,
                 minimum threshold error (set at 0.0001), and operators
                 (including standard ones: +, -, *, %, and sqrt, where %
                 is protected division as well as two other sets the
                 user selects from: set 1: sin and cos; set 2: ln and
                 exp). In addition to protected division, the program
                 also contains these protections:

                 If in (x(y), y = 0, then (x/y) = 1.

                 If in y1/2, y < 0, then y1/2 = -| y|1/2.",
  notes =        "22 August 2004
                 http://ideas.repec.org/p/sce/scecf3/97.html CEF 2003
                 number 97",
}

Genetic Programming entries for Mahmoud A Kaboudan

Citations