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Item Details
| Title:
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INVESTMENT STRATEGIES OPTIMIZATION BASED ON A SAX-GA METHODOLOGY
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| By: |
Antonio M.L. Canelas, Rui F. M. F. Neves, Nuno Horta |
| Format: |
Paperback |
| List price:
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£54.99 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
3642331092 |
| ISBN 13: |
9783642331091 |
| Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
| Pub. date: |
28 September, 2012 |
| Edition: |
2013 ed. |
| Series: |
SpringerBriefs in Applied Sciences and Technology |
| Pages: |
81 |
| Description: |
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. |
| Synopsis: |
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. |
| Illustrations: |
19 Illustrations, color; 62 Illustrations, black and white; XII, 81 p. 81 |
| Publication: |
Germany |
| Imprint: |
Springer-Verlag Berlin and Heidelberg GmbH & Co. K |
| Returns: |
Returnable |
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