Regression Tree-Based Segmentation of Enterprise Value: Bridging Machine Learning and Classical Financial Analysis
Keywords:
Enterprise value, Firm value, Firm size, Machine learning, Regression treeAbstract
In this study, a novel hybrid analytical framework between the regression tree (RT) from machine learning and classical econometrics analysis is presented to understand the relationship between financial parameters and enterprise value (EV). Five predictors, which are: return on equity (ROE), debt-to-asset ratio (DAR), institutional ownership (IO), firm size, and firm age, were examined as independent variables. In particular, the algorithm was applied to split a dataset of 52 Indonesian consumer sector firms, dated from 2018 up to 2023, where then a linear regression model was assigned to each cluster of data. Based on the conducted numerical simulations, it was concluded that ROE and firm size had a consistently positive effect on the EV across all clusters. Meanwhile, the effect of IO, DAR, and age varied on each node. These findings suggest that the relation between financial parameters and firm value (FV) is not uniform and can be interpreted better by considering multi-segment data. This method serves as a new data-driven methodology to the traditional panel analysis, which is complex and requires significant knowledge in analytical statistics.
Downloads
Published
Versions
- 2026-10-22 (2)
- 2026-03-20 (1)
Issue
Section
License
Copyright (c) 2026 Hadi Santoso, Jimmy Tjen (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
License to Publish (Open Access, CC BY 4.0)
1. Warranties
The Author warrants that: the Article is original, has not been submitted simultaneously to any other journal or publisher for consideration, not previously published, not infringing any third-party rights (including copyright, privacy, intellectual property), not confidential; authorship is correct and free of disputes. The Corresponding Author is authorized to sign this Agreement on behalf of all authors and has obtained consent from all co-authors.
2. Copyright Retention
The Author retains full copyright (all intellectual property rights) in and to the Article, including moral rights (authorship, integrity of the work). No copyright is transferred to the Publisher; the Publisher only obtains the license rights specified below.
3. Grant of Publication License
The Author grants Journal of Financial and Economic Dynamics a worldwide, perpetual, non-exclusive, royalty-free license to:
●Publish, reproduce, and distribute the Article in the Journal of Financial and Economic Dynamics;
●Display, transmit, and make the Article publicly accessible via online platforms and digital media;
●Format, edit, and proofread the Article (without altering its core content or meaning);
●Include the Article in indexes, databases, and institutional repositories related to finance and economics.
4. Open Access License (CC BY 4.0)
The Article shall be published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) in the Journal of Financial and Economic Dynamics. This allows any third party to copy, distribute, adapt, and use the Article for any purpose (including commercial use), provided that the original author(s) and the source (Journal of Financial and Economic Dynamics, published by International Natural and Social Science (INSS) Press) are clearly credited.
5. Author’s Rights & Self-Archiving
The Author retains the right to:
●Post the accepted manuscript (pre-publication version) and the final published version of the Article on personal websites, institutional repositories, and academic platforms without any embargo period;
●Use the Article for teaching, research, and academic exchange (non-commercial purposes);
●Include the Article in personal monographs, dissertations, or research reports, with clear citation of the original publication source.
6. Editorial Rights
Journal of Financial and Economic Dynamics reserves the right to conduct text proofreading, format adjustment, and typo correction on the Article, without changing its core content, meaning, or academic rigor. Major revisions to the content shall be discussed and confirmed with the Corresponding Author.
7. Article Processing Charge (APC)
For Open Access publication in the Journal of Financial and Economic Dynamics, the payment and collection of APC shall be subject to the official notification of the Journal (published by Journal of Financial and Economic Dynamics ). No royalty or honorarium shall be paid to the Author for the publication of the Article.
8. Term & Termination
●This Agreement shall take effect upon the Article being accepted for publication in the Journal of Financial and Economic Dynamics and shall remain in effect perpetually, in line with the statutory protection period of copyright.
●If the Article is not published (e.g., rejected after review) or the Author violates the "no multiple submission" rule, this Agreement shall automatically terminate, and all license rights granted to the Publisher shall be revoked.
9. Governing Law
All disputes arising from this Agreement shall be resolved through friendly negotiation first. If negotiation fails, the laws of the jurisdiction where International Natural and Social Science (INSS) Press is located shall apply.
