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Titlebook: Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA; Antonio Daniel Silva,Rui Ferreira Neves,Nuno Horta Book 2

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書目名稱Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA
編輯Antonio Daniel Silva,Rui Ferreira Neves,Nuno Horta
視頻videohttp://file.papertrans.cn/752/751727/751727.mp4
概述Proposes a multi-objective GA to efficiently manage a stock portfolio.Presents results of Evolutionary Computation applied to Computational Finance.Includes supplementary material:
叢書名稱SpringerBriefs in Applied Sciences and Technology
圖書封面Titlebook: Portfolio Optimization Using Fundamental Indicators Based on Multi-Objective EA;  Antonio Daniel Silva,Rui Ferreira Neves,Nuno Horta Book 2
描述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 leve
出版日期Book 2016
關鍵詞Computational Finance; Financial Statements; Fundamental Analysis; Multi-objective evolutionary Algorit
版次1
doihttps://doi.org/10.1007/978-3-319-29392-9
isbn_softcover978-3-319-29390-5
isbn_ebook978-3-319-29392-9Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Author(s) 2016
The information of publication is updating

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