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.
