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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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

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