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Computational Intelligence for Evolving Trading Rules

delete2009-02-01
delete34
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OA
AI
A
Adam Ghandar *
Z
Zbigniew Michalewicz
M
Martin Schmidt
T
Thuy‐Duong Tô
R
Ralf Zurbrugg
DOI:10.1109/TEVC.2008.915992delete
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摘要

摘要

En 中文
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 or applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.
Keyword:
Evolutionary computation
fuzzy systems
portfolio management
stock market
trading systems

期刊

IEEE Transactions on Evolutionary Computation 封面图
IEEE Transactions on Evolutionary Computation
IF:
12
论文数:
1.8K
被引数:
2.4W

机构

U
University of Adelaide
学者数:
2.3W
论文数: 2.4W
被引数: 4.2W
S
schneider electric
学者数:
187
论文数: 140
被引数: 0
P
polsko-japonska akademia technik komputerowych
学者数:
130
论文数: 90
被引数: 0
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