Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia
Building a stock portfolio often requires extensive financial knowledge and Herculean efforts looking at the amount of financial data to analyse. In this study, we utilized Expectation Maximization (EM), K-Means (KM), and Hierarchical Clustering (HC) algorithms to cluster the 38 plantation stocks l...
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| Format: | Article |
| Language: | English |
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Universiti Utara Malaysia Press
2016
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| Online Access: | https://repo.uum.edu.my/id/eprint/24069/1/JICT%2015%202%202016%20%2063%E2%80%9384.pdf |
| _version_ | 1803628655305293824 |
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| author | Keng, Hoong Ng Kok, Chin Khor |
| author_facet | Keng, Hoong Ng Kok, Chin Khor |
| author_sort | Keng, Hoong Ng |
| collection | UUM |
| description | Building a stock portfolio often requires extensive financial knowledge and Herculean efforts looking at the amount of financial data to analyse. In this study, we utilized Expectation
Maximization (EM), K-Means (KM), and Hierarchical Clustering (HC) algorithms to cluster the 38 plantation stocks listed on Bursa Malaysia using 14 financial ratios derived from the fundamental
analysis.The clustering allows investors to profile each resulted cluster statistically and assists them in selecting stocks for their
stock portfolios rapidly.The performance of each cluster was then assessed using 1-year stock price movement.The result showed that a cluster resulted from EM had a better profile and obtained a higher average capital gain as compared with the other
clusters. |
| first_indexed | 2024-07-04T06:25:24Z |
| format | Article |
| id | uum-24069 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:25:24Z |
| publishDate | 2016 |
| publisher | Universiti Utara Malaysia Press |
| record_format | dspace |
| spelling | uum-240692018-04-29T01:43:28Z https://repo.uum.edu.my/id/eprint/24069/ Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia Keng, Hoong Ng Kok, Chin Khor QA75 Electronic computers. Computer science Building a stock portfolio often requires extensive financial knowledge and Herculean efforts looking at the amount of financial data to analyse. In this study, we utilized Expectation Maximization (EM), K-Means (KM), and Hierarchical Clustering (HC) algorithms to cluster the 38 plantation stocks listed on Bursa Malaysia using 14 financial ratios derived from the fundamental analysis.The clustering allows investors to profile each resulted cluster statistically and assists them in selecting stocks for their stock portfolios rapidly.The performance of each cluster was then assessed using 1-year stock price movement.The result showed that a cluster resulted from EM had a better profile and obtained a higher average capital gain as compared with the other clusters. Universiti Utara Malaysia Press 2016 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/24069/1/JICT%2015%202%202016%20%2063%E2%80%9384.pdf Keng, Hoong Ng and Kok, Chin Khor (2016) Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia. Journal of Information and Communication Technology, 15 (2). pp. 63-84. ISSN 2180-3862 http://jict.uum.edu.my/index.php/previous-issues/149-1 |
| spellingShingle | QA75 Electronic computers. Computer science Keng, Hoong Ng Kok, Chin Khor Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia |
| title | Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia |
| title_full | Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia |
| title_fullStr | Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia |
| title_full_unstemmed | Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia |
| title_short | Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia |
| title_sort | evaluation on rapid profiling with clustering algorithms for plantation stocks on bursa malaysia |
| topic | QA75 Electronic computers. Computer science |
| url | https://repo.uum.edu.my/id/eprint/24069/1/JICT%2015%202%202016%20%2063%E2%80%9384.pdf |
| work_keys_str_mv | AT kenghoongng evaluationonrapidprofilingwithclusteringalgorithmsforplantationstocksonbursamalaysia AT kokchinkhor evaluationonrapidprofilingwithclusteringalgorithmsforplantationstocksonbursamalaysia |