Economic and Financial Modeling with Genetic Programming - A Review
Created by W.Langdon from
gp-bibliography.bib Revision:1.8120
- @InCollection{Tuite:2018:ohCEF,
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author = "Cliodhna Tuite and Michael O'Neill and
Anthony Brabazon",
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title = "Economic and Financial Modeling with Genetic
Programming - A Review",
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booktitle = "The Oxford Handbook of Computational Economics and
Finance",
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publisher = "Oxford University Press",
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year = "2018",
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editor = "Shu-Heng Chen and Mak Kaboudan and Ye-Rong Du",
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series = "Oxford Handbooks",
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chapter = "8",
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pages = "266--293",
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keywords = "genetic algorithms, genetic programming, evolutionary
computation, trading rules, price forecasting, stock
selection, derivatives pricing, agent-based modelling",
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isbn13 = "9780199844371",
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URL = "https://global.oup.com/academic/product/the-oxford-handbook-of-computational-economics-and-finance-9780199844371",
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DOI = "doi:10.1093/oxfordhb/9780199844371.013.10",
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size = "29 pages",
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abstract = "This chapter focuses on genetic programming (GP), a
stochastic optimization and model induction technique.
An advantage of GP is that the modeller need not select
the exact parameters to be used in the model
beforehand. Rather, GP can effectively search a complex
model space defined by a set of building blocks
specified by the modeler. This flexibility has allowed
GP to be used for many applications. The chapter
reviews some of the most significant developments using
GP: forecasting, stock selection, derivative pricing
and trading, bankruptcy and credit risk assessment, and
agent-based and economic modelling. Conclusions reached
by studies investigating similar problems do not always
agree; however, GP has proved useful across a wide
range of problem areas. Recent and future work is
increasingly concerned with adapting genetic
programming to more dynamic environments and ensuring
that solutions generalize robustly to out-of-sample
data, to further improve model performance",
- }
Genetic Programming entries for
Cliodhna Tuite
Michael O'Neill
Anthony Brabazon
Citations