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001			85564
003			ES-MaUEC
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008			160211s2016 gw | s |||| 0|eng d
020			_a9783319293929
040			_aES-MaUEC
050		4	_aHG4529.5 _bS558 2016
082	0	4	_a006.3
100	1		_aSilva, Antonio Daniel. _998634 _0Local
245	1	0	_aPortfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA _cby Antonio Daniel Silva, Rui Ferreira Neves, Nuno Horta
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XVII, 95 páginas) _b46 ilustraciones, 18 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_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	3		_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.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650		7	_aFinanzas _0comprobar BNE19900957753 _2embne _9138270
650	0	7	_aAlgoritmos _0 _2embne _9141162
700	1		_aNeves, Rui Ferreira. _998635 _0Local
700	1		_aHorta, Nuno C. G. _0Local _9677277
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-29392-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319293929
907			_a.b12948421 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aHG4529.5 S558 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11591857 _z06-04-17
999			_c85564 _d85564 _x1