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
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;
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
DOI :
10.1109/UKCI.2010.5625600