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Synopsis
This work presents a new approach to portfolio composition in the stock market. It incorporates a fundamental approach using financial ratios and technical indicators with a Multi-Objective Evolutionary Algorithms to choose the portfolio composition with two objectives the return and the risk. Two different chromosomes are used for representing different investment models with real constraints equivalents to the ones faced by managers of mutual funds, hedge funds, and pension funds. To validate the present solution two case studies are presented for the SP&500 for the period June 2010 until end of 2012. The simulations demonstrates that stock selection based on financial ratios is a combination that can be used to choose the best companies in operational terms, obtaining returns above the market average with low variances in their returns. In this case the optimizer found stocks with high return on investment in a conjunction with high rate of growth of the net income and a high profit margin. To obtain stocks with high valuation potential it is necessary to choose companies with a lower or average market capitalization, low PER, high rates of revenue growth and high operating leverage
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- ÉditeurSpringer
- Date d'édition2016
- ISBN 10 3319293907
- ISBN 13 9783319293905
- ReliureBroché
- Langueanglais
- Numéro d'édition1
- Nombre de pages116
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA
Edité par
Springer International Publishing, 2016
ISBN 10 : 3319293907
ISBN 13 : 9783319293905
Neuf
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Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Proposes a multi-objective GA to efficiently manage a stock portfolioPresents results of Evolutionary Computation applied to Computational FinanceProposes a multi-objective GA to efficiently manage a stock portfolioPresents resul. N° de réf. du vendeur 109507289
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA
Edité par
Springer International Publishing, 2016
ISBN 10 : 3319293907
ISBN 13 : 9783319293905
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This work presents a new approach to portfolio composition in the stock market. It incorporates a fundamental approach using financial ratios and technical indicators with a Multi-Objective Evolutionary Algorithms to choose the portfolio composition with two objectives the return and the risk. Two different chromosomes are used for representing different investment models with real constraints equivalents to the ones faced by managers of mutual funds, hedge funds, and pension funds. To validate the present solution two case studies are presented for the SP&500 for the period June 2010 until end of 2012. The simulations demonstrates that stock selection based on financial ratios is a combination that can be used to choose the best companies in operational terms, obtaining returns above the market average with low variances in their returns. In this case the optimizer found stocks with high return on investment in a conjunction with high rate of growth of the net income and a high profit margin. To obtain stocks with high valuation potential it is necessary to choose companies with a lower or average market capitalization, low PER, high rates of revenue growth and high operating leverage. N° de réf. du vendeur 9783319293905
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA
Edité par
Springer International Publishing Feb 2016, 2016
ISBN 10 : 3319293907
ISBN 13 : 9783319293905
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work presents a new approach to portfolio composition in the stock market. It incorporates a fundamental approach using financial ratios and technical indicators with a Multi-Objective Evolutionary Algorithms to choose the portfolio composition with two objectives the return and the risk. Two different chromosomes are used for representing different investment models with real constraints equivalents to the ones faced by managers of mutual funds, hedge funds, and pension funds. To validate the present solution two case studies are presented for the SP&500 for the period June 2010 until end of 2012. The simulations demonstrates that stock selection based on financial ratios is a combination that can be used to choose the best companies in operational terms, obtaining returns above the market average with low variances in their returns. In this case the optimizer found stocks with high return on investment in a conjunction with high rate of growth of the net income and a high profit margin. To obtain stocks with high valuation potential it is necessary to choose companies with a lower or average market capitalization, low PER, high rates of revenue growth and high operating leverage 116 pp. Englisch. N° de réf. du vendeur 9783319293905
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA (SpringerBriefs in Computational Intelligence)
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA
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Portfolio Optimization Using Fundamental Indicators Based on Multi-objective Ea
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA (SpringerBriefs in Computational Intelligence)
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Portfolio Optimization Using Fundamental Indicators Based on Multi-objective Ea
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Portfolio Optimization Using Fundamental Indicators Based on Multi-objective Ea
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Springer-Verlag New York Inc, 2016
ISBN 10 : 3319293907
ISBN 13 : 9783319293905
Neuf
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Paperback. Etat : Brand New. 116 pages. 9.25x6.25x0.50 inches. In Stock. N° de réf. du vendeur x-3319293907
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA (SpringerBriefs in Computational Intelligence)
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Etat : New. N° de réf. du vendeur ABLIING23Mar3113020092669
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