The Syntax of Stock Selection: Grammatical Evolution of a Stock Picking Model
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- @InProceedings{mcgee_etal:cec2010,
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author = "Richard McGee and Michael O'Neill and
Anthony Brabazon",
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title = "The Syntax of Stock Selection: Grammatical Evolution
of a Stock Picking Model",
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booktitle = "2010 IEEE World Congress on Computational
Intelligence",
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pages = "4347--4354",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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isbn13 = "978-1-4244-6910-9",
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DOI = "doi:10.1109/CEC.2010.5586001",
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abstract = "A significant problem in the area of stock selection
is that of identifying the factors that affect a
security's return. While modern portfolio theory
suggests a linear multi-factor model in the form of
Arbitrage Pricing Theory it does not suggest the
identity, or even the number, of risk factors in the
model. Candidate factors for inclusion in a fundamental
model can include hundreds of data points for each firm
and with thousands of firms in the fund manager's
selection universe the model specification problem
encompasses a large, computationally intense search
space. Grammatical Evolution (GE) is a form of
evolutionary computing that has been used successfully
in model induction problems involving large search
spaces. GE is applied to evolve a stock selection model
with a customised mapping process developed
specifically to enhance the performance of evolutionary
operators for this problem. Stock selection models are
rated using fitness functions commonly employed in
asset management; the information coefficient and the
inter-quantile return spread. The findings of the paper
indicate that evolutionary computing is an excellent
tool for the development of stock picking models.",
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notes = "WCCI 2010. Also known as \cite{5586001}",
- }
Genetic Programming entries for
Richard McGee
Michael O'Neill
Anthony Brabazon
Citations