International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
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 Volume 10, Issue 7 (July 2023), Pages: 17-22

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 Original Research Paper

Applying data mining techniques to predict the market performance of publicly traded companies

 Author(s): 

 Vincent Ray O. Boron 1, 2, *, Lyneth Villarba 1, 2, John Vianne Murcia 1, 3, Allemar Jhone Delima 1, 4

 Affiliation(s):

 1Professional Schools, University of Mindanao, Davao City, Davao del Sur, Philippines
 2College of Business and Accounting Education, University of the Immaculate Conception, Philippines
 3College of Business Administration Education, University of Mindanao, Philippines
 4College of Information and Computing Studies, Northern Iloilo State University, Estancia, Iloilo, Philippines

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0001-5645-355X

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2023.07.003

 Abstract:

The advent of the Internet has brought about a transformation in the conventional methods of disseminating company information, presenting corporations with new channels of engagement with investors. Through an analysis of domestic firms listed on the Philippine Stock Exchange (PSE) during the period from 2018 to 2019, this study has probed the Voluntary Disclosure Index (VDI) as an indicator of Internet reporting, discovering that it is influenced by various characteristics of the firm, such as profitability, capital structure, and leverage. Nonetheless, the evidence supporting the impact of internet reporting on market performance remains limited. The objective of this research was to investigate the influence of Internet financial reporting (IFR) on three major market performance indicators: (a) Stock Price, (b) Stock Returns, and (c) Company Value, utilizing the weighted voluntary indexes derived from the VDI checklist. Market data pertaining to 58 publicly listed Philippine companies across various sectors were collected from the PSE database. The study's findings suggest that there are no significant relationships between the domains of the disclosure index and market performance. However, it was observed that the technological features of a company's website can positively influence earnings per share (EPS). By shedding light on the VDI within the context of Philippine companies, this paper makes a valuable contribution to the existing literature. Furthermore, the insights gained from this research could assist regulatory bodies and companies in formulating pertinent policies concerning internet reporting, thereby enhancing corporate governance and the practices of publicly listed companies in the Philippines.

 © 2023 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Data mining, Publicly listed companies, Voluntary disclosure index, Internet reporting, Market performance

 Article History: Received 1 September 2022, Received in revised form 3 May 2023, Accepted 9 May 2023

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Boron VRO, Villarba L, Murcia JV, and Delima AJ (2023). Applying data mining techniques to predict the market performance of publicly traded companies. International Journal of Advanced and Applied Sciences, 10(7): 17-22

 Permanent Link to this page

 Figures

 Fig. 1 

 Tables

 Table 1 Table 2 Table 3 Table 4

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