Investment Strategies Optimization based on a SAX-GA Methodology
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...
Gorde:
| Egile Nagusiak: | , , |
|---|---|
| Formatua: | Livre numérique |
| Hizkuntza: | Anglais |
| Argitaratua: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edizioa: | 1st ed. 2013. |
| Saila: | SpringerBriefs in Computational Intelligence
|
| Sarrera elektronikoa: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Oharra: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Investment Strategies Optimization based on a SAX-GA Methodology, Texte imprimé, 9783642331091 • Investment Strategies Optimization based on a SAX-GA Methodology, Texte imprimé, 9783642331114 • Investment Strategies Optimization based on a SAX-GA Methodology, Texte imprimé, 9783642331091 |
| Gaia: | 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 |
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| Alearen deskribapena: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783642331107 |
| ISSN: | 2625-3712 |
| Sartu: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |