Investment Strategies Optimization based on a SAX-GA Methodology

2013
ISBN: 978-3-642-33109-1
Verlag: Springer

Buch, Englisch, 81 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1591 g

Reihe: SpringerBriefs in Applied Sciences and Technology

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.

Zielgruppe

Research

Autoren/Hrsg.

Canelas, António M. L.

Horta, Nuno C. G.

Neves, Rui F.M.F.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Finanzierung, Investition, Leasing
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Anlagen & Wertpapiere

Inhaltsverzeichnis

Introduction.- Market Analysis Background and Related Work.- SAX-GA Approach.- Results.- Conclusions and Future Work.