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
