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Intelligent financial portfolio composition based on evolutionary computation strategies / António M.S.B.S. Gorgulho, Rui F.M.F. Neves, Nuno C.G. Horta



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Creatore: Gorgulho, António M. S. B. S. Visualizza persona
Titolo: Intelligent financial portfolio composition based on evolutionary computation strategies / António M.S.B.S. Gorgulho, Rui F.M.F. Neves, Nuno C.G. Horta
Link to work: Intelligent financial portfolio composition based on evolutionary computation strategies Visualizza cluster
Pubblicazione: Berlin ; New York : Springer, ©2013
Estensione: 1 online resource : color illustrations.
Tipo formato: computer
Tipo contenuto: text
Tipo supporto: online resource
Disciplina: 332.60285
Titolo uniforme di collana: SpringerBriefs in applied sciences and technology. Computational intelligence.
Genere/Forma: Electronic books
Index term-Uncontrolled: Engineering
Artificial intelligence
Finance
Computational Intelligence
Financial Economics
Soggetto non controllato: Engineering
Artificial intelligence
Finance
Computational Intelligence
Financial Economics
Termine d'indicizzazione-Occupazione: Engineering
Artificial intelligence
Finance
Computational Intelligence
Financial Economics
Classificazione LOC: HG4529.5 .G67 2013
Creatori/Collaboratori: Neves, Rui F. M. F.
Horta, Nuno C. G.
Contenuto supplementare: Includes bibliographical references.
Nota di contenuto: Introduction -- Related work -- Solution's architecture -- System validation -- Conclusions and future work.
Restrizioni accesso: Access is restricted to users affiliated with licensed institutions.
Sommario/riassunto: The management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This subject is becoming popular among computer scientists which try to adapt known Intelligent Computation techniques to the market's domain. This book proposes a potential system based on Genetic Algorithms, which aims to manage a financial portfolio by using technical analysis indicators. The results are promising since the approach clearly outperforms the remaining approaches during the recent market crash.
Collana: SpringerBriefs in applied sciences and technology, Computational intelligence, 2191-530X
ISBN: 9783642329890
3642329896
3642329888
9783642329883
9781283909020
1283909022
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 004625212
Localizzazioni e accesso elettronico https://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=1082630
Collocazione: Electronic access
Lo trovi qui: New York University
Altra ed. diverso supporto: Print version: 9781283909020