Multiobjective portfolio optimization using coherent fuzzy numbers in a credibilistic environment
In this paper, we propose a new credibility function for a fuzzy variable that can accommodate the attitude of the investor (pessimistic, optimistic, or neutral) along with capturing the return expectations. We use an adaptive index, which the investors can use to specify their general perception of...
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Veröffentlicht in: | International journal of intelligent systems 2021-04, Vol.36 (4), p.1560-1594 |
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description | In this paper, we propose a new credibility function for a fuzzy variable that can accommodate the attitude of the investor (pessimistic, optimistic, or neutral) along with capturing the return expectations. We use an adaptive index, which the investors can use to specify their general perception of the financial market. We extend the classic mean‐variance model so that it provides greater flexibility to the investors in specifying their requirements viz., level of diversification, minimum and maximum level of investment in a particular asset, and the skewness requirement. We also replace variance with mean‐absolute semideviation as a measure of quantifying risk, which is more realistic, and solve the resultant multiobjective credibility model with a real‐coded genetic algorithm. Numerical examples have been provided at the end to illustrate the methodology and advantages of the model. |
doi_str_mv | 10.1002/int.22352 |
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Numerical examples have been provided at the end to illustrate the methodology and advantages of the model.</description><subject>coherent fuzzy numbers</subject><subject>credibility function</subject><subject>Genetic algorithms</subject><subject>Intelligent systems</subject><subject>mean–mean sabsolute‐semideviation–skewness model</subject><subject>multiobjective programming</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>real‐coded genetic algorithm</subject><subject>Skewness</subject><subject>Variance</subject><issn>0884-8173</issn><issn>1098-111X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp10LtOwzAUBmALgUQpDLyBJSaGtL4ldkZUcanEZSkSm-W4NrhK7GA7Re3TEygr0xnO958j_QBcYjTDCJG583lGCC3JEZhgVIsCY_x2DCZICFYIzOkpOEtpgxDGnJUToJ6GNrvQbIzObmtgH2K2oXUBhj67zu3VuPVwSM6_Qx0-TDQ-Qzvs9zvoh64xMUHnoYI6mrVrXOtSdhoav3Ux-G7E5-DEqjaZi785Ba93t6vFQ_H4cr9c3DwWmgpECmZLajRnFGFlG6pqjRAveWlKLpitUKkYWQtFiKitqrBVDROIcq7X1jLKKZ2Cq8PdPobPwaQsN2GIfnwpCaspF0RU1aiuD0rHkFI0VvbRdSruJEbyp0E5Nih_Gxzt_GC_XGt2_0O5fF4dEt8gc3Rk</recordid><startdate>202104</startdate><enddate>202104</enddate><creator>Mehlawat, Mukesh K.</creator><creator>Gupta, Pankaj</creator><creator>Khan, Ahmad Z.</creator><general>Hindawi Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-8911-3455</orcidid><orcidid>https://orcid.org/0000-0002-1963-7998</orcidid><orcidid>https://orcid.org/0000-0002-2516-009X</orcidid></search><sort><creationdate>202104</creationdate><title>Multiobjective portfolio optimization using coherent fuzzy numbers in a credibilistic environment</title><author>Mehlawat, Mukesh K. ; Gupta, Pankaj ; Khan, Ahmad Z.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3802-4f53ec74301afb3a9c007575e5784f605a42d8a2289fa61fab480377cdff43733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>coherent fuzzy numbers</topic><topic>credibility function</topic><topic>Genetic algorithms</topic><topic>Intelligent systems</topic><topic>mean–mean sabsolute‐semideviation–skewness model</topic><topic>multiobjective programming</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>real‐coded genetic algorithm</topic><topic>Skewness</topic><topic>Variance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mehlawat, Mukesh K.</creatorcontrib><creatorcontrib>Gupta, Pankaj</creatorcontrib><creatorcontrib>Khan, Ahmad Z.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of intelligent systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mehlawat, Mukesh K.</au><au>Gupta, Pankaj</au><au>Khan, Ahmad Z.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multiobjective portfolio optimization using coherent fuzzy numbers in a credibilistic environment</atitle><jtitle>International journal of intelligent systems</jtitle><date>2021-04</date><risdate>2021</risdate><volume>36</volume><issue>4</issue><spage>1560</spage><epage>1594</epage><pages>1560-1594</pages><issn>0884-8173</issn><eissn>1098-111X</eissn><abstract>In this paper, we propose a new credibility function for a fuzzy variable that can accommodate the attitude of the investor (pessimistic, optimistic, or neutral) along with capturing the return expectations. 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subjects | coherent fuzzy numbers credibility function Genetic algorithms Intelligent systems mean–mean sabsolute‐semideviation–skewness model multiobjective programming Multiple objective analysis Optimization real‐coded genetic algorithm Skewness Variance |
title | Multiobjective portfolio optimization using coherent fuzzy numbers in a credibilistic environment |
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