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Item Details
Title: PORTFOLIO OPTIMIZATION USING FUNDAMENTAL INDICATORS BASED ON MULTI-OBJECTIVE EA
By: Antonio Silva, Rui F. M. F. Neves, Nuno Horta
Format: Paperback

List price: £44.99
Our price: £39.37
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ISBN 10: 3319293907
ISBN 13: 9783319293905
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Publisher: SPRINGER INTERNATIONAL PUBLISHING AG
Pub. date: 11 February, 2016
Edition: 1st ed. 2016
Series: SpringerBriefs in Applied Sciences and Technology
Pages: 95
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
Illustrations: 18 Illustrations, color; 28 Illustrations, black and white; XVII, 95 p. 46
Publication: Switzerland
Imprint: Springer International Publishing AG
Returns: Returnable
Some other items by this author:
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ANALOG CIRCUITS AND SYSTEMS OPTIMIZATION BASED ON EVOLUTIONARY COMPUTATION TECHNIQUES (HB)
ANALOG CIRCUITS AND SYSTEMS OPTIMIZATION BASED ON EVOLUTIONARY COMPUTATION TECHNIQUES (PB)
ANALOG IC PLACEMENT GENERATION VIA NEURAL NETWORKS FROM UNLABELED DATA
ANALOG INTEGRATED CIRCUIT DESIGN AUTOMATION (HB)
AUTOMATIC ANALOG IC SIZING AND OPTIMIZATION CONSTRAINED WITH PVT CORNERS AND LAYOUT EFFECTS (HB)
COMMANDING THE LIGHT (PB)
FINANCIAL DATA RESAMPLING FOR MACHINE LEARNING BASED TRADING
FUNDAMENTOS DA ODONTOLOGIA EM AMBIENTE HOSPITALAR / UTI
GENERATING ANALOG IC LAYOUTS WITH LAYGEN II (PB)
IDENTIFYING PATTERNS IN FINANCIAL MARKETS (PB)
INTELLIGENT FINANCIAL PORTFOLIO COMPOSITION BASED ON EVOLUTIONARY COMPUTATION STRATEGIES (PB)
INVESTMENT STRATEGIES OPTIMIZATION BASED ON A SAX-GA METHODOLOGY (PB)
LOGARITHMIC VOLTAGE-TO-TIME CONVERTER FOR ANALOG-TO-DIGITAL SIGNAL CONVERSION (HB)
MACHINE LEARNING BASED PAIRS TRADING INVESTMENT STRATEGY
PARALLEL GENETIC ALGORITHMS FOR FINANCIAL PATTERN DISCOVERY USING GPUS (PB)
SPEEDING-UP RADIO-FREQUENCY INTEGRATED CIRCUIT SIZING WITH NEURAL NETWORKS
STOCK EXCHANGE TRADING USING GRID PATTERN OPTIMIZED BY A GENETIC ALGORITHM WITH SPECIATION
TUNABLE LOW-POWER LOW-NOISE AMPLIFIER FOR HEALTHCARE APPLICATIONS
USING ARTIFICIAL NEURAL NETWORKS FOR ANALOG INTEGRATED CIRCUIT DESIGN AUTOMATION

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