DocumentCode :
2325518
Title :
Objective function design in a grammatical evolutionary trading system
Author :
Bradley, Robert ; Brabazon, Anthony ; O´Neill, Michael
Author_Institution :
Natural Comput. Res. & Applic. Group, Univ. Coll. Dublin, Dublin, Ireland
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
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. A number of experiments were performed to assess the effect of objective function design on the trading characteristics of the evolved trading strategies. Empirical results suggest that the choice of objective function has a significant impact. The paper concludes with in and out-of-sample results, and indicates a number of avenues of future work.
Keywords :
commerce; genetic algorithms; evolved trading strategies; grammar-based genetic programming; grammatical evolutionary trading system; objective function design; trading model induction; Algorithm design and analysis; Biological system modeling; Data models; Evolutionary computation; Mathematical model; Measurement; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
Type :
conf
DOI :
10.1109/CEC.2010.5586020
Filename :
5586020
Link To Document :
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