An effective technique for automatic portfolio stock selection, diversification, and optimization

An effective technique for automatic portfolio stock selection, diversification, and optimization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An effective technique for automatic portfolio stock selection, diversification, and optimization Mmabusulane P Monamo, Bhekisipho Twala, Jan Harm Chrisiaan Pretorius This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4689352/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In this paper, a novel stock-to-sector-to-benchmark ratio or anomaly that assists investors in automating stock selection, diversification, and optimization for portfolio management is introduced. The approach uses three market capitalization values, one for the individual stock, one for the sector, and one for the benchmark capitalization, to calculate the ratio. The results of this paper prove the efficacy of the proposed methodology. Out of the eleven constructed for the period under study, all the portfolios constructed beat the benchmark in terms of the highest weighted returns, lowest risk, and highest Sharpe ratio during the sample period (1979 to 2019). Fama‒French three-factor and five-factor models are used to assess whether the factor loadings influence performance. Although the Fama-French three-factor models showed a statistically significant alpha, the asset pricing model had an average adjusted R 2 of 13%, while the adjusted R 2 of the Fama-French five-factor model had an average of 60% (excluding a single stock-based portfolio). These portfolios exhibit a statistically significant negative SMB, which implies that the performance of the portfolios is affected by large capitalization stocks, which is in direct contrast to the popular belief that outperformance is influenced mainly by small-cap stocks. Financial Mathematics market efficiency capital market portfolio optimization Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4689352","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":322941846,"identity":"abce6fdd-4b3e-471b-910f-02612561da2c","order_by":0,"name":"Mmabusulane P Monamo","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-2065-977X","institution":"University of Johannesburg","correspondingAuthor":true,"prefix":"","firstName":"Mmabusulane","middleName":"P","lastName":"Monamo","suffix":""},{"id":322941847,"identity":"10877054-8da3-49e9-a4ba-f486f9b7d04a","order_by":1,"name":"Bhekisipho Twala","email":"","orcid":"https://orcid.org/0000-0002-3452-9581","institution":"Tshwane University of Technolgy","correspondingAuthor":false,"prefix":"","firstName":"Bhekisipho","middleName":"","lastName":"Twala","suffix":""},{"id":322941848,"identity":"b4c832ed-28b8-4922-b092-abc5a74e18db","order_by":2,"name":"Jan Harm Chrisiaan Pretorius","email":"","orcid":"https://orcid.org/0000-0002-2023-749X","institution":"University of Johannesburg","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"Harm Chrisiaan","lastName":"Pretorius","suffix":""}],"badges":[],"createdAt":"2024-07-05 03:34:59","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4689352/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4689352/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59820006,"identity":"3022c4af-0357-4666-b62c-30af8c5db883","added_by":"auto","created_at":"2024-07-08 03:22:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":534249,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptJuly2024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4689352/v1_covered_e5247293-d515-4ca8-9dfb-58f38205c6f3.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eAn effective technique for automatic portfolio stock selection, diversification, and optimization\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"market efficiency, capital market, portfolio optimization","lastPublishedDoi":"10.21203/rs.3.rs-4689352/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4689352/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this paper, a novel stock-to-sector-to-benchmark ratio or anomaly that assists investors in automating stock selection, diversification, and optimization for portfolio management is introduced. The approach uses three market capitalization values, one for the individual stock, one for the sector, and one for the benchmark capitalization, to calculate the ratio. The results of this paper prove the efficacy of the proposed methodology. Out of the eleven constructed for the period under study, all the portfolios constructed beat the benchmark in terms of the highest weighted returns, lowest risk, and highest Sharpe ratio during the sample period (1979 to 2019). Fama‒French three-factor and five-factor models are used to assess whether the factor loadings influence performance. Although the Fama-French three-factor models showed a statistically significant alpha, the asset pricing model had an average adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e of 13%, while the adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e of the Fama-French five-factor model had an average of 60% (excluding a single stock-based portfolio). 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