Stock Portfolio Evaluation: An Application of Genetic-Programming-Based Technical Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InCollection{wagman:2003:SPEAAGTA,
  author =       "Liad Wagman",
  title =        "Stock Portfolio Evaluation: An Application of
                 Genetic-Programming-Based Technical Analysis",
  booktitle =    "Genetic Algorithms and Genetic Programming at Stanford
                 2003",
  year =         "2003",
  editor =       "John R. Koza",
  pages =        "213--220",
  address =      "Stanford, California, 94305-3079 USA",
  month =        "4 " # dec,
  publisher =    "Stanford Bookstore",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.genetic-programming.org/sp2003/Wagman.pdf",
  size =         "8 pages",
  abstract =     "Recent studies in financial economics suggest that
                 technical analysis may have merit to predictability of
                 stock. When attempting to create an efficient portfolio
                 of stocks, there are numerous factors to consider. The
                 problem is that the evaluation involves many
                 qualitative factors, which causes most approximations
                 to go off track. This paper presents a genetic
                 programming approach to portfolio evaluation. By using
                 a set of fitness heuristics over a population of stock
                 portfolios, the goal is to find a portfolio that has a
                 high expected return over investment.",
  notes =        "part of \cite{koza:2003:gagp}",
}

Genetic Programming entries for Liad Wagman

Citations