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| Online-Ressource |
Verfasst von: | Doloc, Cris [VerfasserIn]  |
Titel: | Applications of computational intelligence in data-driven trading |
Verf.angabe: | Cris Doloc |
Verlagsort: | Hoboken, New Jersey |
Verlag: | Wiley |
E-Jahr: | 2020 |
Jahr: | [2020] |
Umfang: | 1 online resource (xv, 272 pages) |
Fussnoten: | Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on December 16, 2019) |
ISBN: | 1-119-55052-1 |
| 978-1-119-55052-5 |
| 978-1-119-55050-1 |
Abstract: | "The objective of this book is to introduce the reader to the field of Computational Finance using the framework of Machine Learning as a tool of scientific inquiry. It is an attempt to integrate these two topics: how to use Machine Learning as the tool of choice in solving topical problems in Computational Finance. Readers will learn modern methods used by financial engineers and quantitative analysts to access, process, and interpret data. Throughout, there are case studies that are representative of relevant problems in modern finance. Topics covered include Time Series analysis, forecasting, Dynamic Programming, and Neural Networks"-- |
URL: | Aggregator: https://learning.oreilly.com/library/view/-/9781119550501/?ar |
Datenträger: | Online-Ressource |
Sprache: | eng |
Bibliogr. Hinweis: | Erscheint auch als : Druck-Ausgabe |
Sach-SW: | Ingénierie financière ; Études de cas |
| Intelligence informatique ; Études de cas |
| Apprentissage automatique ; Études de cas |
| Computational intelligence |
| Financial engineering |
| Machine learning |
| Case studies |
K10plus-PPN: | 1903894158 |
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Lokale URL UB: | Zum Volltext |
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| Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
| Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich |
Bibliothek/Idn: | UW / m4585400990 |
Lokale URL Inst.: | Zum Volltext |
1-119-55052-1,978-1-119-55052-5,978-1-119-55050-1
Applications of computational intelligence in data-driven trading / Doloc, Cris [VerfasserIn]; [2020] (Online-Ressource)
69258400