Financial Health and Growth Valuation under the GARP Framework: Evidence from TMUS, AT&T, and Verizon

Lingqian Meng

doi:10.54254/2754-1169/2026.NJ30054

Advances in Economics, Management and Political SciencesOpen access

Financial Health and Growth Valuation under the GARP Framework: Evidence from TMUS, AT&T, and Verizon

Research Article

Open Access

Financial Health and Growth Valuation under the GARP Framework: Evidence from TMUS, AT&T, and Verizon

Lingqian Meng ^1*

¹ University of Glasgow

^*Corresponding author: lingqianmeng407@gmail.com

Published on 26 November 2025

AEMPS Vol.242

ISSN (Print): 2754-1177

ISSN (Online): 2754-1169

ISBN (Print): 978-1-80590-555-4

ISBN (Online): 978-1-80590-556-1

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Abstract

As the world's financial system matures, investors are finding it increasingly difficult to find among the wide range of stocks that offer lasting growth at a significant price. To solve this problem, an in-depth analysis of T-mobile (TMUS), AT&T (T) and Verizon (VZ) is conducted in this article. Based on fundamental analysis and data from the Altman Z-score model, the investment value of these three companies is evaluated using the Growth at a Reasonable Price (GARP) investment strategy model. This analysis conducts a comprehensive assessment of the company's financial status through three key aspects: growth, valuation, and stability. Further analysis of the Z-score results and five-year return forecasts provides multi-level comparisons for investment performance. The research results show that the three companies have certain differences in terms of financial structure and growth consistency. TMUS has demonstrated a good balance between profitability and leverage ratio. This effectively reflects its market value with long-term profit potential. In contrast, T demonstrated stronger profit performance, but its reinvestment flexibility was limited. However, VZ's revenue expansion was relatively slow and it was under greater financial pressure, performing the worst. Overall, this study provides the practical application value of GARP for investors who pursue data-driven decision-making. In addition, this study further extends the empirical application of the GARP strategy to the wireless communication industry, providing reference ideas for identifying companies that combine growth potential with financial stability in the market based on industry characteristics.

Keywords:

GARP, TMUS, Financial Health, Growth Valuation

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References

[1]. Priyanto, P. (2021). The Value of GARP Investing: Evidence from the Indonesian Stock Exchange. JABE (JOURNAL of ACCOUNTING and BUSINESS EDUCATION), 5(2), 9.

[2]. Gottwald, R. (2012). The Use of Indicators in Modified Historical Model to Estimate the Intrinsic Value of a Stock. Journal of Competitiveness, 4(2), 97–110.

[3]. James, N., & Agung, A. (2023). Systematic Literature Review: Fundamental Analysis of Company Operational Health. 2023 International Workshop on Artificial Intelligence and Image Processing (IWAIIP), 385–390.

[4]. Puspa Dewi Yulianty, Mugayat, A., & Anggun Nur’aeni. (2024). Unravelling the Impact of Fundamental Analysis on Stock Prices: A Study of Banking Companies Listed on the Indonesia Stock Exchange, 2017-2021. The International Journal of Business Review (the Jobs Review), 6(2).

[5]. Altman, E. I. (2018). Applications of Distress Prediction Models: What Have We Learned After 50 Years from the Z-Score Models? International Journal of Financial Studies, 6(3), 70.

[6]. Drakopoulou, V. (2016). A Review of Fundamental and Technical Stock Analysis Techniques. Journal of Stock & Forex Trading, 05(1).

[7]. Baresa, S., Bogdan, S., & Ivanovic, Z. (2013). Strategy of stock valuation by fundamental analysis. UTMS Journal of Economics, 4(1), 45–51.

[8]. Patalay, S., & Bandlamudi, M. R. (2021). Decision Support System for Stock Portfolio Selection Using Artificial Intelligence and Machine Learning. Ingénierie Des Systèmes D Information, 26(1), 87–93.

[9]. Siddiqui, S. A. (2012). Business Bankruptcy Prediction Models: A Significant Study of the Altman’s Z-Score Model. SSRN Electronic Journal, 3(1).

[10]. Zacks Investment Research. (2025). VZ: Verizon Communications - Detailed Earnings Estimates - Zacks.com. Zacks Investment Research.

References

[1]. Priyanto, P. (2021). The Value of GARP Investing: Evidence from the Indonesian Stock Exchange. JABE (JOURNAL of ACCOUNTING and BUSINESS EDUCATION), 5(2), 9.

[2]. Gottwald, R. (2012). The Use of Indicators in Modified Historical Model to Estimate the Intrinsic Value of a Stock. Journal of Competitiveness, 4(2), 97–110.

[5]. Altman, E. I. (2018). Applications of Distress Prediction Models: What Have We Learned After 50 Years from the Z-Score Models? International Journal of Financial Studies, 6(3), 70.

[6]. Drakopoulou, V. (2016). A Review of Fundamental and Technical Stock Analysis Techniques. Journal of Stock & Forex Trading, 05(1).

[7]. Baresa, S., Bogdan, S., & Ivanovic, Z. (2013). Strategy of stock valuation by fundamental analysis. UTMS Journal of Economics, 4(1), 45–51.

[9]. Siddiqui, S. A. (2012). Business Bankruptcy Prediction Models: A Significant Study of the Altman’s Z-Score Model. SSRN Electronic Journal, 3(1).

[10]. Zacks Investment Research. (2025). VZ: Verizon Communications - Detailed Earnings Estimates - Zacks.com. Zacks Investment Research.

Cite this article

Meng,L. (2025). Financial Health and Growth Valuation under the GARP Framework: Evidence from TMUS, AT&T, and Verizon. Advances in Economics, Management and Political Sciences,242,27-34.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-BPS 2026 Symposium: Sustainability Transitions and Regional Economic Restructuring in New Contexts

ISBN: 978-1-80590-555-4(Print) / 978-1-80590-556-1(Online)

Editor: Canh Thien Dang, Xiaohui Hu

Conference website: https://www.confbps.org/Nanjing.html

Conference date: 9 January 2026

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.242

ISSN: 2754-1169(Print) / 2754-1177(Online)

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