Alpha191 and Volatility Dual Factor Model Quantitative Strategy

Alpha191 and Volatility Dual Factor Model Quantitative Strategy | 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Article Alpha191 and Volatility Dual Factor Model Quantitative Strategy Yunfan ZHANG This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8708191/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 This study constructs a composite strategy based on the Alpha191 momentum factor and the volatility factor. Through backtesting analysis of a single product and a full product portfolio, the effectiveness of the factor combination strategy and its applicable boundaries are systematically examined. The study found that in a single product scenario, the composite factor strategy exhibits significant synergy, and its risk-adjusted return is significantly better than that of a single factor strategy, confirming the good complementarity between the momentum factor and the volatility factor. However, when the strategy is extended to a full product portfolio, the performance advantage of the composite factor is significantly attenuated, which reveals the limitations of the fixed-weight combination strategy in cross-product applications. In-depth analysis shows that the volatility factor can effectively suppress the extreme risk exposure of the momentum factor, but the heterogeneity of the market environment will lead to structural changes in the correlation of factors. Based on this, this study proposes improvement directions from the dimensions of dynamic optimization and adaptive adjustment of factor combinations, providing a theoretical basis and practical path for the development of more robust quantitative strategies. Finance quantitive finance fintech factor strategy stock finance market 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-8708191","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581010510,"identity":"ae2663a6-1fb3-494b-be74-3532607ed1e2","order_by":0,"name":"Yunfan ZHANG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBAC9gbmhgNAmp+faC08BxjBWiRnNpCiBURLbjhAtBb2xsbDPH8OSxgfT97A8KNiGxFaeA42HJzBc1jC7MyzAsaeM7cJa7GXSGw48EHicJ3ZjRwDZsY2IrTwyD9sOJBgAHTYDKK1SABD7EPCYQkDCaK18CQC/XIgXUIC6JeDRPmFh/3w4c88f6wl+NuTNz74UUGEFihoBuIEgwNEqweCOrAWUnSMglEwCkbBCAIAMqlAGfybmFQAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0000-8285-0700","institution":"Macau University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Yunfan","middleName":"","lastName":"ZHANG","suffix":""}],"badges":[],"createdAt":"2026-01-27 09:01:17","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-8708191/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8708191/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101296919,"identity":"9bd6de25-815b-4426-a68b-2805c7451f36","added_by":"auto","created_at":"2026-01-28 09:23:16","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":727558,"visible":true,"origin":"","legend":"","description":"","filename":"Forecast.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8708191/v1_covered_e0e39538-ebac-4486-8da9-13b0f9a81f97.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eAlpha191 and Volatility Dual Factor Model Quantitative Strategy\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Macau University of Science and Technology","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":"quantitive finance, fintech, factor strategy, stock, finance market","lastPublishedDoi":"10.21203/rs.3.rs-8708191/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8708191/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study constructs a composite strategy based on the Alpha191 momentum factor and the volatility factor. 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