Strategic Investment in BIST100: A Machine Learning Approach Using Symbolic Aggregate Approximation Clustering
| dc.contributor.author | Nalici, Mehmet Eren | |
| dc.contributor.author | Soylemez, Ismet | |
| dc.contributor.author | Unlu, Ramazan | |
| dc.contributor.other | 01. Abdullah Gül University | |
| dc.contributor.other | 02.02. Endüstri Mühendisliği | |
| dc.contributor.other | 02. Mühendislik Fakültesi | |
| dc.contributor.other | 07. Fen Bilimleri Enstitüsü | |
| dc.contributor.other | 07.03. Endüstri Mühendisliği Anabilim Dalı | |
| dc.date.accessioned | 2025-09-25T10:57:41Z | |
| dc.date.available | 2025-09-25T10:57:41Z | |
| dc.date.issued | 2025 | |
| dc.description | Nalici, Mehmet Eren/0000-0002-7954-6916 | en_US |
| dc.description.abstract | This study employs the Symbolic Aggregate Approximation (SAX) clustering method to enhance investor decision-making on the Borsa Istanbul (BIST100) by identifying companies exhibiting analogous stock movements. The data from 81 BIST100 companies over a three-year period has been analyzed, with a focus on risk minimization and strategic investment. The SAX method, integrated with a dendrogram, categorizes stocks into sector-based and non-sector-based clusters, providing insights for portfolio optimization. The results demonstrate the effectiveness of the method in identifying relevant stock patterns across sectors, aiding in more informed investment decisions. This approach highlights the need for considering multiple factors in investment strategies, offering a new perspective on stock market analysis with advanced clustering techniques. | en_US |
| dc.identifier.doi | 10.23055/ijietap.2025.32.2.10273 | |
| dc.identifier.issn | 1072-4761 | |
| dc.identifier.issn | 1943-670X | |
| dc.identifier.scopus | 2-s2.0-105001969547 | |
| dc.identifier.uri | https://doi.org/10.23055/ijietap.2025.32.2.10273 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12573/4690 | |
| dc.language.iso | en | en_US |
| dc.publisher | Univ Cincinnati industrial Engineering | en_US |
| dc.relation.ispartof | International Journal of Industrial Engineering-Theory Applications and Practice | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Bist100 | en_US |
| dc.subject | Financial Access | en_US |
| dc.subject | Machine Learning | en_US |
| dc.subject | Stock Market | en_US |
| dc.subject | Symbolic Aggregate Approximation (SAX) | en_US |
| dc.title | Strategic Investment in BIST100: A Machine Learning Approach Using Symbolic Aggregate Approximation Clustering | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | Nalici, Mehmet Eren/0000-0002-7954-6916 | |
| gdc.author.institutional | Nalici, Mehmet Eren | |
| gdc.author.institutional | Söylemez, İsmet | |
| gdc.author.institutional | Ünlü, Ramazan | |
| gdc.author.scopusid | 59725388900 | |
| gdc.author.scopusid | 57198896486 | |
| gdc.author.scopusid | 57197769375 | |
| gdc.author.wosid | Söylemez, Ismet/Aag-4835-2021 | |
| gdc.author.wosid | Nalici, Mehmet Eren/Htr-2909-2023 | |
| gdc.author.wosid | Ünlü, Ramazan/C-3695-2019 | |
| gdc.author.wosid | Nalici, Mehmet Eren/Htr-2909-2023 | |
| gdc.description.department | Abdullah Gül University | en_US |
| gdc.description.departmenttemp | [Nalici, Mehmet Eren; Soylemez, Ismet; Unlu, Ramazan] Abdullah Gul Univ, Dept Ind Engn, Kayseri, Turkiye | en_US |
| gdc.description.endpage | 395 | en_US |
| gdc.description.issue | 2 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q3 | |
| gdc.description.startpage | 382 | en_US |
| gdc.description.volume | 32 | en_US |
| gdc.description.woscitationindex | Science Citation Index Expanded | |
| gdc.description.wosquality | Q4 | |
| gdc.identifier.wos | WOS:001489890300001 | |
| gdc.opencitations.count | 0 | |
| gdc.plumx.mendeley | 7 | |
| gdc.plumx.scopuscites | 1 | |
| gdc.scopus.citedcount | 1 | |
| gdc.wos.citedcount | 2 | |
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