Identifying Patterns in Financial Markets [electronic resource] : New Approach Combining Rules Between PIPs and SAX / by João Leitão, Rui Ferreira Neves, Nuno C.G. Horta.
Tipo de material:
TextoSeries SpringerBriefs in Computational IntelligenceEditor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XVII, 66 p. 69 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319701608Tema(s): Computational intelligence | Algorithms | Economics, Mathematical | Pattern recognition | Computational Intelligence | Algorithm Analysis and Problem Complexity | Quantitative Finance | Pattern RecognitionFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónico
Contenidos:
En: Springer Nature eBookResumen: 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.
Introduction -- Related Work -- SIR/GA approach -- Case studies.
| Tipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
|---|---|---|---|---|---|---|---|
| Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | 1 | No para préstamo |
Acceso multiusuario
Introduction -- Related Work -- SIR/GA approach -- Case studies.
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.
UABC ; Temporal ; 01/01/2021-12/31/2023.
