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Intelligent Financial Portfolio Composition based on Evolutionary Computation Strategies: SpringerBriefs in Applied Sciences and Technology

Autor Antonio Gorgulho, Rui F. M. F. Neves, Nuno C. G. Horta
en Limba Engleză Paperback – 27 sep 2012
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.
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Specificații

ISBN-13: 9783642329883
ISBN-10: 3642329888
Pagini: 92
Ilustrații: XI, 77 p. 30 illus., 15 illus. in color.
Dimensiuni: 155 x 235 x 5 mm
Greutate: 0.14 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile SpringerBriefs in Applied Sciences and Technology, SpringerBriefs in Computational Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Preface.- Introduction.- Related Work.- Solution’s Architecture.- System Validation.- Conclusions and Future Work.- References.- Appendixes.

Textul de pe ultima copertă

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.

Caracteristici

Proposes genetic algorithms to manage financial porfolios Provides information to predict the future movement of a stock’s Interdisciplinary content of interest to a broad range of researchers and professionials, from computer scientists to economists Includes supplementary material: sn.pub/extras