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The accuracy of financial distress prediction models in various Indonesian industrial companies

W Wardhiah(1), Zulkifli Yusuf(2), N Nuslima(3), R Rasyimah(4), Ghazali Syamni(5Mail), Khairuddin Yahya(6),
(1) Universitas Malikussaleh, Aceh, 24355, Indonesia
(2) Universitas Malikussaleh, Aceh, 24355, Indonesia
(3) Universitas Malikussaleh, Aceh, 24355, Indonesia
(4) Universitas Malikussaleh, Aceh, 24355, Indonesia
(5) Universitas Malikussaleh, Aceh, 24355, Indonesia
(6) Universitas Malikussaleh, Aceh, 24355, Indonesia

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Abstract


Market participants use the forecast of the financial crisis as an indication and early warning system. This study aims to examine the efficacy of eight models for predicting bankruptcy in Indonesian industrial enterprises. Secondary data from various industrial sector companies listed on the IDX for the 2016–2020 timeframe was utilized in this study. The approach employed in this study, which is not based on the Z-Score from 1968, the Revised Z-Score from 1984, the Z-Score Modified from 1995, Springate from 1978, Ohlson from 1980, Zmijewski from 1983, Fulmer from 1984, or Grover from 2001, is a quantitative descriptive study method. Fulmer's model was proven to be foreseeable by the study's findings, and Grover and Almant improved it to make it more accurate than competing prediction models.


Keywords


financial distress; accuracy; various industry; Indonesia

   

Article DOI



DOI: https://doi.org/10.33122/ijase.v5i1.246
       

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Article Pages


Pages: 14-20

   

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References


Adnan Aziz, M., & Dar, H. A. (2006). Predicting corporate bankruptcy: where we stand? Corporate Governance: The International Journal of Business In Society, 6(1), 18-33. Retrieved from https://doi.org/10.1108/14720700610649436. doi:10.1108/14720700610649436

Agrawal, K., & Maheshwari, Y. (2019). Efficacy of industry factors for corporate default prediction. IIMB Management Review, 31(1), 71-77. Retrieved from https://www.sciencedirect.com/science/article/pii/S0970389618304609. doi:https://doi.org/10.1016/j.iimb.2018.08.007

Alam, T. M., Shaukat, K., Mushtaq, M., Ali, Y., Khushi, M., Luo, S., & Wahab, A. (2020). Corporate bankruptcy prediction: An approach towards better corporate world. The Computer Journal, 64(11), 1731-1746. Retrieved from https://doi.org/10.1093/comjnl/bxaa056. doi:10.1093/comjnl/bxaa056

Andreou, C. K., Andreou, P. C., & Lambertides, N. (2021). Financial distress risk and stock price crashes. Journal of Corporate Finance, 67, 101870. doi:https://doi.org/10.1016/j.jcorpfin.2020.101870

Arroyave, J. (2018). A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia. Journal of International Studies, 11(1).

B?rbu??-Mi?u, N., & Madaleno, M. (2020). Assessment of bankruptcy risk of large companies: European Countries evolution analysis. Journal of Risk and Financial Management, 13(3), 58. Retrieved from https://www.mdpi.com/1911-8074/13/3/58.

Bateni, L., & Asghari, F. (2020). Bankruptcy prediction using logit and genetic algorithm models: A comparative analysis. Computational Economics, 55(1), 335-348. Retrieved from https://doi.org/10.1007/s10614-016-9590-3. doi:10.1007/s10614-016-9590-3

Begovi?, S. V., Boni?, L., & Jovin, S. (2020). A comparison of the bankruptcy prediction models on a sample of Serbian companies. Teme, 503-518. doi:https://doi.org/10.22190/TEME180619036V

Chen, C.-C., Chen, C.-D., & Lien, D. (2020). Financial distress prediction model: The effects of corporate governance indicators. Journal of Forecasting, 39(8), 1238-1252. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2684. doi:https://doi.org/10.1002/for.2684

ElBannan, M. A. (2021). On the prediction of financial distress in emerging markets: What matters more? Empirical evidence from Arab spring countries. Emerging Markets Review, 47, 100806. Retrieved from https://www.sciencedirect.com/science/article/pii/S1566014121000145. doi:https://doi.org/10.1016/j.ememar.2021.100806

Idress, S., & Qayyum, A. (2018). The impact of financial distress risk on equity returns: A case study of non-financial firms of Pakistan Stock Exchange. 2018, 5(2), 11. Retrieved from http://www.kspjournals.org/index.php/JEB/article/view/1623. doi:10.1453/Jeb. v5i2.1623

Indriyanti, M. (2019). The accuracy of financial sistress prediction models: Empirical study on the World’s 25 Biggest Tech Companies in 2015–2016 Forbes’s version. KnE Social Sciences, 3(11). Retrieved from https://knepublishing.com/index.php/KnE-Social/article/view/4025. doi:10.18502/kss.v3i11.4025

Jayanti, Q., & Rustiana, R. (2015). Analisis tingkat akurasi model-model prediksi kebangkrutan untuk memprediksi voluntary auditor switching (Studi pada perusahaan manufaktur yang terdaftar di BEI). Modus, 27(2), 87-122.

Junaeni, I. (2018). Stock prices predicted by bankruptcy condition? Binus Business Review, 9(2), 105-114. doi:https://doi.org/10.21512/bbr.v9i2.4103

Karas, M., & Srbová, P. (2019). Predicting bankruptcy in construction business: Traditional model validation and formulation of a new model. Journal of International Studies, 12(1).

Kesuma, M. R., Defung, F., & Kusumawardani, A. (2021). Bankruptcy prediction and its effect on stock prices as impact of the COVID-19 pandemic. Technium Soc. Sci. J., 25, 567.

Kliestik, T., Vrbka, J., & Rowland, Z. (2018). Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis. Equilibrium. Quarterly Journal of Economics and Economic Policy, 13(3), 569-593. doi: https://doi.org/10.24136/eq.2018.028

Matenda, F. R., Sibanda, M., Chikodza, E., & Gumbo, V. (2021). Bankruptcy prediction for private firms in developing economies: a scoping review and guidance for future research. Management Review Quarterly. Retrieved from https://doi.org/10.1007/s11301-021-00216-x. doi:10.1007/s11301-021-00216-x

Nugroho, M., Arif, D., & Halik, A. (2021). The effect of financial distress on stock returns, through systematic risk and profitability as mediator variables. Accounting, 7(7), 1717-1724.

Pham Vo Ninh, B., Do Thanh, T., & Vo Hong, D. (2018). Financial distress and bankruptcy prediction: An appropriate model for listed firms in Vietnam. Economic Systems, 42(4), 616-624. doi:https://doi.org/10.1016/j.ecosys.2018.05.002

Platt, H. D., & Platt, M. B. (2006). Understanding differences between financial distress and bankruptcy. Review of Applied Economics, 2(1076-2016-87135), 141-157.

Prasetiyani, E., & Sofyan, M. (2020). Bankruptcy analysis using Altman Z-score model and Springate model in retail trading company listed in Indonesia Stock Exchange. Ilomata International Journal of Tax and Accounting, 1(3), 139-144.

Prusak, B. (2018). Review of research into enterprise bankruptcy prediction in selected Central and Eastern European Countries. International Journal of Financial Studies, 6(3), 60. Retrieved from https://www.mdpi.com/2227-7072/6/3/60.

Sareen, A., & Sharma, S. (2022). Assessing financial distress and predicting stock prices of automotive sector: Robustness of Altman Z-score. Vision, 26(1), 11-24.

Sarumpaet, T. L. (2021). The influence of bankruptcy prediction using the Altman Z Score Modified approach to stock prices (Survey of private companies in the general banking sector in the Indonesia Stock Exchange in 2015-2018). Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(8), 428-434. doi:https://doi.org/10.17762/turcomat.v12i8.2818

Sun, J., Li, H., Huang, Q.-H., & He, K.-Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. Knowledge-Based Systems, 57, 41-56. doi:https://doi.org/10.1016/j.knosys.2013.12.006

Susilowati, E., & Simangunsong, J. M. (2019). Financial distress, bankruptcy analysis and implications for stock prices of consumer goods companies in Indonesia. Relevance: Journal of Management and Business, 2(2).

Syamni, G., Majid, M. S. A., & Siregar, W. V. (2018). Bankruptcy prediction models and stock prices of the coal mining industry in Indonesia. Etikonomi, 17(1), 57-68.

Thinh, T. Q., Tuan, D. A., Huy, N. T., & Thu, T. N. A. (2021). Financial distress prediction of listed companies–empirical evidence on the Vietnamese stock market. Innovations, 17(2), 377-388.

Tristanti, B. I., & Hendrawan, R. (2020, 2020/02/07). Z-Score or S-Score Model is better to predict financial distress?: Test in State-Owned Enterprise listed in IDX. Paper presented at the Proceedings of the 3rd Global Conference On Business, Management, and Entrepreneurship (GCBME 2018).

Ullah, H., Wang, Z., Abbas, M. G., Zhang, F., Shahzad, U., & Mahmood, M. R. (2021). Association of financial distress and predicted bankruptcy: The case of Pakistani banking sector. The Journal of Asian Finance, Economics and Business, 8(1), 573-585.

Vochozka, M., Vrbka, J., & Suler, P. (2020). Bankruptcy or Success? The Effective Prediction of a Company’s Financial Development Using LSTM. Sustainability, 12(18), 7529. Retrieved from https://www.mdpi.com/2071-1050/12/18/7529.

Wieprow, J., & Gawlik, A. (2021). The Use of discriminant analysis to assess the risk of bankruptcy of enterprises in crisis conditions using the example of the tourism sector in Poland. Risks, 9(4), 78. Retrieved from https://www.mdpi.com/2227-9091/9/4/78.


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Copyright (c) 2023 Wardhiah, Zulkifli Yusuf, Nuslima, Rasyimah, Ghazali Syamni*, Khairuddin Yahya

International Journal of Advances in Social and Economics (IJASE) | E-ISSN: 2685-2691