1. ZHAW digitalcollection
  2. School of Management and Law
  3. Publikationen
  4. Publikationen School of Management and Law
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-30520
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSutiene, Kristina-
dc.contributor.authorSchwendner, Peter-
dc.contributor.authorSipos, Ciprian-
dc.contributor.authorLorenzo, Luis-
dc.contributor.authorMirchev, Miroslav-
dc.contributor.authorLameski, Petre-
dc.contributor.authorKabasinskas, Audrius-
dc.contributor.authorTidjani, Chemseddine-
dc.contributor.authorOzturkkal, Belma-
dc.contributor.authorCerneviciene, Jurgita-
dc.date.accessioned2024-04-26T12:33:35Z-
dc.date.available2024-04-26T12:33:35Z-
dc.date.issued2024-04-08-
dc.identifier.issn2624-8212de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/30520-
dc.description.abstractBuilding an investment portfolio is a problem that numerous researchers have addressed for many years. The key goal has always been to balance risk and reward by optimally allocating assets such as stocks, bonds, and cash. In general, the portfolio management process is based on three steps: planning, execution, and feedback, each of which has its objectives and methods to be employed. Starting from Markowitz's mean-variance portfolio theory, different frameworks have been widely accepted, which considerably renewed how asset allocation is being solved. Recent advances in artificial intelligence provide methodological and technological capabilities to solve highly complex problems, and investment portfolio is no exception. For this reason, the paper reviews the current state-of-the-art approaches by answering the core question of how artificial intelligence is transforming portfolio management steps. Moreover, as the use of artificial intelligence in finance is challenged by transparency, fairness and explainability requirements, the case study of post-hoc explanations for asset allocation is demonstrated. Finally, we discuss recent regulatory developments in the European investment business and highlight specific aspects of this business where explainable artificial intelligence could advance transparency of the investment process.de_CH
dc.language.isoende_CH
dc.publisherFrontiers Research Foundationde_CH
dc.relation.ispartofFrontiers in Artificial Intelligencede_CH
dc.rightshttps://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectPortfoliode_CH
dc.subjectAsset allocationde_CH
dc.subjectArtificial intelligencede_CH
dc.subjectMachine learningde_CH
dc.subjectOptimizationde_CH
dc.subjectRebalancingde_CH
dc.subjectExplainabilityde_CH
dc.subjectRegulationde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.subject.ddc332.6: Investitionde_CH
dc.titleEnhancing portfolio management using artificial intelligence : literature reviewde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitut für Wealth & Asset Management (IWA)de_CH
dc.identifier.doi10.3389/frai.2024.1371502de_CH
dc.identifier.doi10.21256/zhaw-30520-
zhaw.funding.euNode_CH
zhaw.issue1371502de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume7de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Management and Law

Files in This Item:
File Description SizeFormat 
2024_Sutiene-etal_Enhancing-portfolio-management-artificial-intelligence_frai.pdf1.74 MBAdobe PDFThumbnail
View/Open
Show simple item record
Sutiene, K., Schwendner, P., Sipos, C., Lorenzo, L., Mirchev, M., Lameski, P., Kabasinskas, A., Tidjani, C., Ozturkkal, B., & Cerneviciene, J. (2024). Enhancing portfolio management using artificial intelligence : literature review. Frontiers in Artificial Intelligence, 7(1371502). https://doi.org/10.3389/frai.2024.1371502
Sutiene, K. et al. (2024) ‘Enhancing portfolio management using artificial intelligence : literature review’, Frontiers in Artificial Intelligence, 7(1371502). Available at: https://doi.org/10.3389/frai.2024.1371502.
K. Sutiene et al., “Enhancing portfolio management using artificial intelligence : literature review,” Frontiers in Artificial Intelligence, vol. 7, no. 1371502, Apr. 2024, doi: 10.3389/frai.2024.1371502.
SUTIENE, Kristina, Peter SCHWENDNER, Ciprian SIPOS, Luis LORENZO, Miroslav MIRCHEV, Petre LAMESKI, Audrius KABASINSKAS, Chemseddine TIDJANI, Belma OZTURKKAL und Jurgita CERNEVICIENE, 2024. Enhancing portfolio management using artificial intelligence : literature review. Frontiers in Artificial Intelligence. 8 April 2024. Bd. 7, Nr. 1371502. DOI 10.3389/frai.2024.1371502
Sutiene, Kristina, Peter Schwendner, Ciprian Sipos, Luis Lorenzo, Miroslav Mirchev, Petre Lameski, Audrius Kabasinskas, Chemseddine Tidjani, Belma Ozturkkal, and Jurgita Cerneviciene. 2024. “Enhancing Portfolio Management Using Artificial Intelligence : Literature Review.” Frontiers in Artificial Intelligence 7 (1371502). https://doi.org/10.3389/frai.2024.1371502.
Sutiene, Kristina, et al. “Enhancing Portfolio Management Using Artificial Intelligence : Literature Review.” Frontiers in Artificial Intelligence, vol. 7, no. 1371502, Apr. 2024, https://doi.org/10.3389/frai.2024.1371502.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.