This book presents a new computational finance approach combining a
Symbolic Aggregate approximation (SAX) technique with an
optimization kernel based on genetic algorithms (GA). While the SAX
representation is used to describe the financial time series, the
evolutionary optimization kernel is used in order to identify the
most relevant patterns and generate investment rules. The proposed
approach considers several different chromosomes structures in
order to achieve better results on the trading platform The
methodology presented in this book has great potential on
investment markets.
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