000 | 03287nam a22005535i 4500 | ||
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001 | 978-3-319-29392-9 | ||
003 | DE-He213 | ||
005 | 20200421111844.0 | ||
007 | cr nn 008mamaa | ||
008 | 160211s2016 gw | s |||| 0|eng d | ||
020 |
_a9783319293929 _9978-3-319-29392-9 |
||
024 | 7 |
_a10.1007/978-3-319-29392-9 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aCOM004000 _2bisacsh |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aSilva, Antonio Daniel. _eauthor. |
|
245 | 1 | 0 |
_aPortfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA _h[electronic resource] / _cby Antonio Daniel Silva, Rui Ferreira Neves, Nuno Horta. |
250 | _a1st ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
300 |
_aXVII, 95 p. 46 illus., 18 illus. in color. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X |
|
505 | 0 | _aIntroduction -- Literature Review -- System Architecture -- Multi-Objective optimization -- Simulations in single and multi-objective optimization -- Outlook. | |
520 | _aThis 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. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aFinance. | |
650 | 0 | _aAlgorithms. | |
650 | 0 | _aEconomics, Mathematical. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
650 | 2 | 4 | _aQuantitative Finance. |
650 | 2 | 4 | _aFinance, general. |
700 | 1 |
_aNeves, Rui Ferreira. _eauthor. |
|
700 | 1 |
_aHorta, Nuno. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319293905 |
830 | 0 |
_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-29392-9 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c55719 _d55719 |