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Books > Computing & IT > General theory of computing > Data structures
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA (Paperback, 1st ed. 2016)
Loot Price: R1,750
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Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA (Paperback, 1st ed. 2016)
Series: SpringerBriefs in Computational Intelligence
Expected to ship within 10 - 15 working days
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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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