DocumentCode :
2910405
Title :
An empirical study of collaboration methods for coevolving technical trading rules
Author :
Adamu, Kamal ; Phelps, Steve
Author_Institution :
Center for Comput. Finance & Economic Agents, Univ. of Essex, Colchester, UK
fYear :
2010
fDate :
8-10 Sept. 2010
Firstpage :
1
Lastpage :
6
Abstract :
Coevolutionary algorithms employ collaboration methods in assessing the fitness of solutions. In this paper, we explore four different collaboration methods for coevolving technical trading rules for entering, and exiting long and short positions, and stop loss rules for long and short positions respectively. Our results show that our problem is sensitive to the collaboration method being used and that an averaging method with more than one collaborator from each species is most efficient for our problem.
Keywords :
financial data processing; groupware; coevolving technical trading rule; collaboration method; stop loss rules; Collaboration; Companies; Genetics; Grammar; Security; Silicon;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence (UKCI), 2010 UK Workshop on
Conference_Location :
Colchester
Print_ISBN :
978-1-4244-8774-5
Electronic_ISBN :
978-1-4244-8773-8
Type :
conf
DOI :
10.1109/UKCI.2010.5625600
Filename :
5625600
Link To Document :
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