The Self-Evolving Logic of Financial Claim Prices
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @InProceedings{RePEc:sce:scecf7:102,
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author = "Thomas H. Noe",
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title = "The Self-Evolving Logic of Financial Claim Prices",
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booktitle = "Third International Conference on Computing in
Economics and Finance",
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year = "1997",
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editor = "Kenneth L. Judd",
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address = "Stanford, California, USA",
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month = jun # " 30 - " # jul # " 2",
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organisation = "Society of Computational Economics",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://bucky.stanford.edu/cef97/abstracts/noe.html",
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URL = "http://ideas.repec.org/p/sce/scecf7/102.html",
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abstract = "we will price financial claims by allowing option
pricing programs to evolve trough time via combining
with each other, mutating randomly, and reproducing at
rates based on the pressure of evolutionary selection.
The specific technique we employ is Genetic
Programming, an optimisation technique based on the
principles of natural selection. Compared to the
traditional arbitrage-based approach, this technique is
useful when the underlying asset dynamics are unknown
or when the pricing equations are too complicated to
solve analytically. Compared to other established
data-driven option pricing techniques such as neural
networks, implied binomial trees, etc., genetic
programming has the advantage of not restricting the
structure of the pricing formulas, formulae themselves
evolve rather than simply the parameters of a single
formula. Our analysis is preliminary. However, by
showing that genetic programming can recover
Black-Sholes formula from a fairly small data sample,
we hope to validate the ability of genetic programming
approaches to consistently and efficiently estimate
option prices, at least in structurally simple
environments. Future research will apply genetic
programming approach to more intractable problems in
derivative asset pricing.",
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notes = "CEF 1997 number 102 http://bucky.stanford.edu/cef97/",
- }
Genetic Programming entries for
Thomas H Noe
Citations