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100   $a20140317d2014      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aFuzzy Portfolio Optimization $eAdvances in Hybrid Multi-criteria Methodologies /$fby Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
205   $a1st ed. 2014.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2014.
215   $a1 online resource (XVI, 320 p. 56 illus., 2 illus. in color.) 
225 1 $aStudies in Fuzziness and Soft Computing,$x1434-9922 ;$v316
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-642-54651-X 
320   $aIncludes bibliographical references (pages 311-317) and index.
327   $aPortfolio optimization: an overview -- Portfolio optimization with interval coefficients -- Portfolio optimization in fuzzy environment -- Possibilistic programming approaches to portfolio optimization -- Portfolio optimization using credibility theory -- Multi-criteria fuzzy portfolio optimization -- Suitability considerations in multi-criteria fuzzy portfolio optimization-I -- Suitability considerations in multi-criteria fuzzy portfolio optimization-II -- Ethicality considerations in multi-criteria fuzzy portfolio optimization -- Multi-criteria portfolio optimization using support vector machines and genetic algorithms.
330   $aThis monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean?variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuing advanced research and/or engaged in practical issues in the rapidly evolving field of portfolio optimization.  .
410  0$aStudies in Fuzziness and Soft Computing,$x1434-9922 ;$v316
606   $aComputational intelligence
606   $aMathematical optimization
606   $aEconomics
606   $aManagement science
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008
606   $aEconomics, general$3https://scigraph.springernature.com/ontologies/product-market-codes/W00000
615  0$aComputational intelligence.
615  0$aMathematical optimization.
615  0$aEconomics.
615  0$aManagement science.
615 14$aComputational Intelligence.
615 24$aOptimization.
615 24$aEconomics, general.
676   $a006.3
700   $aGupta$b Pankaj$4aut$4http://id.loc.gov/vocabulary/relators/aut$0732693
702   $aMehlawat$b Mukesh Kumar$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aInuiguchi$b Masahiro$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aChandra$b Suresh$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910299727703321
996   $aFuzzy Portfolio Optimization$92165814
997   $aUNINA