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Investment Strategies Optimization based on a SAX-GA Methodology

António M.L. Canelas, Rui F.M.F. Neves, Nuno C.G. Horta (Autoren)

Buch | Softcover

XII, 81 Seiten

2012 | 2013
Springer Berlin (Verlag)
978-3-642-33109-1 (ISBN)

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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.

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

From the reviews:

"The book is accessible by anyone with a broad knowledge of statistics and algorithms, and an interest in finance. The nicely done, comprehensive illustrations make this complicated subject easy to understand, and compensate for the often-clumsy sentence structure. I recommend the book ... ." (Martin Gfeller, Computing Reviews, May, 2013)

Erscheint lt. Verlag	28.9.2012
Reihe/Serie	SpringerBriefs in Applied Sciences and Technology
Reihe/Serie	SpringerBriefs in Computational Intelligence
Zusatzinfo	XII, 81 p. 81 illus., 19 illus. in color.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	168 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Technik
	Wirtschaft ► Betriebswirtschaft / Management
	Wirtschaft ► Volkswirtschaftslehre ► Finanzwissenschaft
Schlagworte	Financial Market • frequent patterns • Genetic Algorithm • Genetische Algorithmen • Pattern Discovery • pattern recognition • Quantitative Finance • SAX Representation
ISBN-10	3-642-33109-2 / 3642331092
ISBN-13	978-3-642-33109-1 / 9783642331091
Zustand	Neuware