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Decision Support Systems in Stock Investment Problems

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dc.creator Tükel, Gözde Özkan
dc.creator KÖSE, Utku
dc.creator Tükel, Tolga
dc.date 2023-01-01T00:00:00Z
dc.date.accessioned 2025-02-25T10:33:03Z
dc.date.available 2025-02-25T10:33:03Z
dc.identifier 8126a76a-df09-4b6e-8e16-28b3848329ec
dc.identifier 10.37394/23209.2023.20.43
dc.identifier https://avesis.sdu.edu.tr/publication/details/8126a76a-df09-4b6e-8e16-28b3848329ec/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/100337
dc.description This study compiles decision support systems that aim to optimize financial decision processes by examining the literature studies targeting stock investments. The review encompasses a range of methodologies and applications, from traditional approaches such as Markowitz’s Modern Portfolio Theory, Black-Litterman, and Single Index models to artificial intelligence-based techniques. In detail, the contributions of Decision Support Systems to stock portfolio construction and portfolio optimization processes along with comparative analyses between these systems are scrutinized. The review also aims to enable researchers and practitioners to be engaged in portfolio optimization with a framework for future investigations in areas such as historical data analysis, future price movement prediction, assessment of risk factors, and determination of optimal portfolio distribution. Furthermore, it seeks to enhance the understanding of decision support systems employed in portfolio optimization, facilitating a more comprehensive grasp of their utility within stock investments.
dc.language eng
dc.rights info:eu-repo/semantics/openAccess
dc.title Decision Support Systems in Stock Investment Problems
dc.type info:eu-repo/semantics/article


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