K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES
This study employs k-means clustering and agglomerative hierarchical clustering techniques to visually examine the potential relationship between Environmental Social and Governance (ESG) scores, their year-over-year variations, and annual stock returns for a sample of 34 energy sector companies ope...
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| Format: | Article |
| Language: | English |
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Institutul de Studii Financiare
2023-06-01
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| Series: | Revista de Studii Financiare |
| Subjects: | |
| Online Access: | https://revista.isfin.ro/wp-content/uploads/2023/06/11.-Rusu-et-al..pdf |
| _version_ | 1797663350540206080 |
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| author | Ștefan Rusu Marcel Ioan Boloș Marius Leordeanu |
| author_facet | Ștefan Rusu Marcel Ioan Boloș Marius Leordeanu |
| author_sort | Ștefan Rusu |
| collection | DOAJ |
| description | This study employs k-means clustering and agglomerative hierarchical clustering techniques to visually examine the potential relationship between Environmental Social and Governance (ESG) scores, their year-over-year variations, and annual stock returns for a sample of 34 energy sector companies operating in Europe and the United States. While the agglomerative hierarchical clustering dendrogram suggests two clusters, the elbow method of the k-means algorithm suggests 2-4 clusters. The results indicate that neither ESG scores nor their year-on-year variations had an impact on the annual returns of the stocks. The conclusion is further confirmed by the Pearson correlation coefficient. However, the ESG scores of European energy companies show a tighter dispersion and smaller year-over-year change, making them more predictable ESG score-wise and thus, potentially, more attractive to ESG-driven investors. |
| first_indexed | 2024-03-11T19:13:15Z |
| format | Article |
| id | doaj.art-98052623e6304353be33ce619706cd7f |
| institution | Directory Open Access Journal |
| issn | 2537-3714 2559-1347 |
| language | English |
| last_indexed | 2024-03-11T19:13:15Z |
| publishDate | 2023-06-01 |
| publisher | Institutul de Studii Financiare |
| record_format | Article |
| series | Revista de Studii Financiare |
| spelling | doaj.art-98052623e6304353be33ce619706cd7f2023-10-09T09:32:29ZengInstitutul de Studii FinanciareRevista de Studii Financiare2537-37142559-13472023-06-018Special16618010.55654/JFS.2023.SP.11K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATESȘtefan Rusu0Marcel Ioan Boloș1Marius Leordeanu2University of Oradea, Oradea, RomaniaUniversity of Oradea, Oradea, RomaniaPolytechnic University of Bucharest, Bucharest, Romania; The Institute of Mathematics of the Romanian Academy, Bucharest, RomaniaThis study employs k-means clustering and agglomerative hierarchical clustering techniques to visually examine the potential relationship between Environmental Social and Governance (ESG) scores, their year-over-year variations, and annual stock returns for a sample of 34 energy sector companies operating in Europe and the United States. While the agglomerative hierarchical clustering dendrogram suggests two clusters, the elbow method of the k-means algorithm suggests 2-4 clusters. The results indicate that neither ESG scores nor their year-on-year variations had an impact on the annual returns of the stocks. The conclusion is further confirmed by the Pearson correlation coefficient. However, the ESG scores of European energy companies show a tighter dispersion and smaller year-over-year change, making them more predictable ESG score-wise and thus, potentially, more attractive to ESG-driven investors.https://revista.isfin.ro/wp-content/uploads/2023/06/11.-Rusu-et-al..pdfstock marketclusteringesgmachine learningk-means clusteringagglomerative hierarchical clustering |
| spellingShingle | Ștefan Rusu Marcel Ioan Boloș Marius Leordeanu K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES Revista de Studii Financiare stock market clustering esg machine learning k-means clustering agglomerative hierarchical clustering |
| title | K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES |
| title_full | K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES |
| title_fullStr | K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES |
| title_full_unstemmed | K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES |
| title_short | K-MEANS AND AGGLOMERATIVE HIERARCHICAL CLUSTERING ANALYSIS OF ESG SCORES, YEARLY VARIATIONS, AND STOCK RETURNS: INSIGHTS FROM THE ENERGY SECTOR IN EUROPE AND THE UNITED STATES |
| title_sort | k means and agglomerative hierarchical clustering analysis of esg scores yearly variations and stock returns insights from the energy sector in europe and the united states |
| topic | stock market clustering esg machine learning k-means clustering agglomerative hierarchical clustering |
| url | https://revista.isfin.ro/wp-content/uploads/2023/06/11.-Rusu-et-al..pdf |
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