Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/52599
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Type: Journal article
Title: Computational intelligence for evolving trading rules
Author: Ghandar, A.
Michalewicz, Z.
Schmidt, M.
To, T.
Zurbrugg, R.
Citation: IEEE Transactions on Evolutionary Computation, 2009; 13(1):71-86
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2009
ISSN: 1089-778X
1941-0026
Statement of
Responsibility: 
Adam Ghandar, Zbigniew Michalewicz, Martin Schmidt, Thuy-Duong Tô, and Ralf Zurbrugg
Abstract: This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.
Keywords: evolutionary computation; fuzzy systems; portfoliomanagement; stock market; trading systems
Description: Copyright © 2008 IEEE
RMID: 0020090158
DOI: 10.1109/TEVC.2008.915992
Appears in Collections:Computer Science publications

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