Machine Learning Models to Predict Shareholder Returns in the Banking Industry
Proceedings of the 13th International Conference on Information Technology and Its Applications (CITA 2024); pp: 283-294
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| Język: | English |
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Vietnam-Korea University of Information and Communication Technology
2024
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| Dostęp online: | https://elib.vku.udn.vn/handle/123456789/4040 |
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| Thư viện lưu trữ: | Trường Đại học Công nghệ Thông tin và Truyền thông Việt Hàn - Đại học Đà Nẵng |
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oai:elib.vku.udn.vn:123456789-40402024-07-31T03:41:40Z Machine Learning Models to Predict Shareholder Returns in the Banking Industry Le, Duc Thinh Nguyen, Phuong Anh Machine learning Commercial banking Metric Panel data Shareholder return Proceedings of the 13th International Conference on Information Technology and Its Applications (CITA 2024); pp: 283-294 Competitive pressures have steadily driven commercial banks to strategically focus on generating returns to shareholders. This research article purpose is to analyze and provide a summary about the impacts of key financial ratios (key metrics) on the effectiveness and efficiency of commercial banking industry, which reflects on the shareholder return of these banks, using machine learning and the official data of the banking industry in the USA. In this article, we study key metrics for commercial banks, and analyze annual financial and operating data of some biggest, publicly traded commercial banks in the USA in order to find out some predictive models using machine learning algorithms, particularly for panel data, and therefore, to give investors, shareholders, or asset managers a reliable tool to evaluate and forecast the performance of commercial banks. 2024-07-31T03:41:37Z 2024-07-31T03:41:37Z 2024-07 Working Paper 978-604-80-9774-5 https://elib.vku.udn.vn/handle/123456789/4040 en CITA; application/pdf Vietnam-Korea University of Information and Communication Technology |
| institution |
Trường Đại học Công nghệ Thông tin và Truyền thông Việt Hàn - Đại học Đà Nẵng |
| collection |
DSpace |
| language |
English |
| topic |
Machine learning Commercial banking Metric Panel data Shareholder return |
| spellingShingle |
Machine learning Commercial banking Metric Panel data Shareholder return Le, Duc Thinh Nguyen, Phuong Anh Machine Learning Models to Predict Shareholder Returns in the Banking Industry |
| description |
Proceedings of the 13th International Conference on Information Technology and Its Applications (CITA 2024); pp: 283-294 |
| format |
Working Paper |
| author |
Le, Duc Thinh Nguyen, Phuong Anh |
| author_facet |
Le, Duc Thinh Nguyen, Phuong Anh |
| author_sort |
Le, Duc Thinh |
| title |
Machine Learning Models to Predict Shareholder Returns in the Banking Industry |
| title_short |
Machine Learning Models to Predict Shareholder Returns in the Banking Industry |
| title_full |
Machine Learning Models to Predict Shareholder Returns in the Banking Industry |
| title_fullStr |
Machine Learning Models to Predict Shareholder Returns in the Banking Industry |
| title_full_unstemmed |
Machine Learning Models to Predict Shareholder Returns in the Banking Industry |
| title_sort |
machine learning models to predict shareholder returns in the banking industry |
| publisher |
Vietnam-Korea University of Information and Communication Technology |
| publishDate |
2024 |
| url |
https://elib.vku.udn.vn/handle/123456789/4040 |
| _version_ |
1849203348575617024 |