Identifying Patterns in Financial Markets [electronic resource] : New Approach Combining Rules Between PIPs and SAX /
By: Leitão, João [author.].
Contributor(s): Neves, Rui Ferreira [author.] | Horta, Nuno C.G [author.] | SpringerLink (Online service).
Series: SpringerBriefs in Computational Intelligence: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVII, 66 p. 69 illus. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319701608.Subject(s): Computer Engineering
| Computational Intelligence | Algorithm Analysis and Problem Complexity | Quantitative Finance | Pattern RecognitionDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: This book describes a new pattern discovery approach based on the combination among rules between Perceptually Important Points (PIPs) and the Symbolic Aggregate approximation (SAX) representation optimized by Genetic Algorithm (GA). The proposed approach was tested with real data from S&P500 index and all the results obtained outperform the Buy&Hold strategy. Three different case studies are presented by the authors.
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This book describes a new pattern discovery approach based on the combination among rules between Perceptually Important Points (PIPs) and the Symbolic Aggregate approximation (SAX) representation optimized by Genetic Algorithm (GA). The proposed approach was tested with real data from S&P500 index and all the results obtained outperform the Buy&Hold strategy. Three different case studies are presented by the authors.
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