Investor Protection in Indonesia: Financial Ratios as Early Warning Indicators
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Keywords

Financial distress prediction
Emerging Market
Indonesia stock exchange
Investor protection

How to Cite

Enggar Sukma Kinanthi, & Sukmawati Sukamulja. (2025). Investor Protection in Indonesia: Financial Ratios as Early Warning Indicators . Journal of Economics, Business, and Accountancy Ventura, 27(3), 445-460. https://doi.org/10.14414/jebav.v27i3.4851
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

The Indonesian government aims to enhance public engagement in the capital market
by strengthening investor protection and financial literacy through the establishment
of a Watchlist Board. This study identifies the most effective financial ratios for dis
tinguishing between the performance of LQ45 and Watchlist Board firms. Using dis
criminant analysis, the research examines a sample of 43 firms from the LQ45 index
and 43 firms from the Watchlist Board between 2020 and 2022. The findings reveal
four key financial ratios with strong differentiating power: Total Asset Growth, Re
turn on Assets (ROA), Operating Cash Flow (OCF) to Current Liabilities, and OCF
to Total Liabilities. Additionally, the study develops a predictive model that can fore
cast company performance and serve as an early warning system for investors. Build
ing on prior research in this area, the results highlight the critical role of profitability,
efficient resource allocation, and robust corporate governance in fostering financial
stability and safeguarding investor interests. This study not only provides a practical
predictive model but also offers valuable insights for interpreting these financial ratios,
particularly in the context of investor protection within emerging markets, such as
Indonesia.

References

Adinegara, G., & Sukamulya, S. (2021). The Effect of Good Corporate Governance on the Market Value of Financial Sector Companies in Indonesia. Jurnal Akuntansi Dan Keuangan, 23(2), 83–94. https://doi.org/10.9744/jak.23.2.83-94

Almeida, H., Campello, M., & Weisbach, M. S. (2005). The Cash Flow Sensitivity of Cash. SSRN Electronic Journal, November 2002. https://doi.org/10.2139/ssrn.345840

Altman, E. I., Danovi, A., Falini, A., & Altman, E. (2013). Z-Score Models’ Application to Italian Companies Subject to Extraordinary Administration. Journal of Applied Finance, 23(1), 1–10. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2686750

Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., & Suvas, A. (2017). Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman’s Z-Score Model. Journal of International Financial Management and Accounting, 28(2), 131–171. https://doi.org/10.1111/jifm.12053

Bates, T. W., Kahle, K. M., & Stulz, R. M. (2009). Why Do U. S. Firms Hold So Much than They Used To? Journal of Finance, 64(5), 1985–2021.