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Computational Intelligence for Evolving Trading Rules
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DOI：10.1109/TEVC.2008.915992.png)
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Abstract
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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.
Keywords:
Evolutionary computation
fuzzy systems
portfolio management
stock market
trading systems
Journal
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12
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1.8K
Citations:
2.4W
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