Stock Portfolio Evaluation: An Application of Genetic-Programming-Based Technical Analysis
Created by W.Langdon from
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- @InCollection{wagman:2003:SPEAAGTA,
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author = "Liad Wagman",
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title = "Stock Portfolio Evaluation: An Application of
Genetic-Programming-Based Technical Analysis",
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booktitle = "Genetic Algorithms and Genetic Programming at Stanford
2003",
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year = "2003",
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editor = "John R. Koza",
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pages = "213--220",
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address = "Stanford, California, 94305-3079 USA",
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month = "4 " # dec,
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publisher = "Stanford Bookstore",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://www.genetic-programming.org/sp2003/Wagman.pdf",
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size = "8 pages",
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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.",
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notes = "part of \cite{koza:2003:gagp}",
- }
Genetic Programming entries for
Liad Wagman
Citations