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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)"Sobre este título" puede pertenecer a otra edición de este libro.
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Descripción Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 96 pp. Englisch. Nº de ref. del artículo: 9783642331091
Descripción Paperback. Condición: Brand New. 2013 edition. 90 pages. 9.00x6.00x0.25 inches. In Stock. Nº de ref. del artículo: x-3642331092
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Descripción Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783642331091
Descripción Condición: New. 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. . 2012. 2013th Edition. Paperback. . . . . Nº de ref. del artículo: V9783642331091
Descripción Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a new computational finance approach combining SAX and GA Shows soft computing and computational intelligence as solutions for financial markets Case studies presented help identifying the investment strategy to apply in different . Nº de ref. del artículo: 5057158
Descripción Condición: New. 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. . 2012. 2013th Edition. Paperback. . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9783642331091