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