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Investment Strategies Optimization Based on a SAX-GA Methodology
Canelas, Antonio M.L.; Neves, Rui F.M.F.; Horta, Nuno C.G.
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Description for Investment Strategies Optimization Based on a SAX-GA Methodology
Paperback. Presents a computational finance approach combining a Symbolic Aggregate approximation technique with an optimization kernel based on genetic algorithms. This book uses the SAX representation to describe the financial time series, the evolutionary optimization kernel is used in order to identify the relevant patterns and generate investment rules. Series: SpringerBriefs in Applied Sciences and Technology/ SpringerBriefs in Computational Intelligence. Num Pages: 93 pages, 62 black & white illustrations, 19 colour illustrations, biography. BIC Classification: KFFM; PBUD; UYQ. Category: (P) Professional & Vocational. Dimension: 238 x 156 x 6. Weight in Grams: 166.
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.
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.
Product Details
Format
Paperback
Publication date
2012
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
90
Condition
New
Series
SpringerBriefs in Applied Sciences and Technology/ SpringerBriefs in Computational Intelligence
Number of Pages
81
Place of Publication
Berlin, Germany
ISBN
9783642331091
SKU
V9783642331091
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Investment Strategies Optimization Based on a SAX-GA Methodology
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)