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Investment Strategies Optimization based on a SAX-GA Methodology
Author(s) -
António Canelas,
Rui Neves,
Nuno Horta
Publication year - 2012
Publication title -
springerbriefs in applied sciences and technology
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.111
H-Index - 15
eISSN - 2191-5318
pISSN - 2191-530X
DOI - 10.1007/978-3-642-33110-7
Subject(s) - investment (military) , computer science , business , political science , law , politics
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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