Objective function design in a grammatical evolutionary trading system

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Title: Objective function design in a grammatical evolutionary trading system
Authors: Bradley, Robert
Brabazon, Anthony
O'Neill, Michael
Permanent link: http://hdl.handle.net/10197/2740
Date: Jul-2010
Abstract: Designing a suitable objective function is an essential step in successfully applying an evolutionary algorithm to a problem. In this study we apply a grammar-based Genetic Programming algorithm called Grammatical Evolution to the problem of trading model induction and carry out a number of experiments to assess the effect of objective function design on the trading characteristics of the evolved strategies. The paper concludes with in and out-of-sample results, and indicates a number of avenues of future work.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE Press
Copyright (published version): 2010 IEEE
Keywords: Trading systemsObjective function designGrammatical evolution
Subject LCSH: Evolutionary computation
Genetic algorithms
Genetic programming (Computer science)
DOI: 10.1109/CEC.2010.5586020
Other versions: http://dx.doi.org/10.1109/CEC.2010.5586020
Language: en
Status of Item: Peer reviewed
Is part of: 2010 IEEE Congress on Evolutionary Computation (CEC) [proceedings]
Conference Details: Congress on Evolutionary Computation, IEEE World Congress on Computational Intelligence, Barcelona, Spain, 18-23 July
ISBN: 978-1-4244-6909-3
Appears in Collections:FMC² Research Collection
Computer Science Research Collection
Business Research Collection

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