Intelligent Financial Portfolio Composition based on Evolutionary Computation Strategies [electronic resource] / by Antonio Gorgulho, Rui F.M.F. Neves, Nuno C.G. Horta.

By:

Gorgulho, Antonio [author.]

Contributor(s):

Material type: Text

TextSeries: SpringerBriefs in Applied Sciences and TechnologyPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: XI, 77 p. 30 illus., 15 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783642329890

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

006.3 23

LOC classification:

Q342

Online resources:

Click here to access online

Contents:

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

In: Springer eBooksSummary: 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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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
E-Book	Central Library		Available		E-49587

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

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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