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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Hlavní autoři:	Le, Duc Thinh, Nguyen, Phuong Anh
Médium:	Bài viết
Jazyk:	English
Vydáno:	Vietnam-Korea University of Information and Communication Technology 2024
Témata:	Machine learning Commercial banking Metric Panel data Shareholder return
On-line přístup:	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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spelling	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

Machine Learning Models to Predict Shareholder Returns in the Banking Industry

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