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Journal of Information and Optimization Sciences cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Open Access Research Article

Altman’s Z-model an approach to predict the financial distress of selected companies of Tata Group in India

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pp. 1637–1651Vol. 45Issue 6September 2024DOI: 10.47974/JIOS-1639XML
Received:
11 Apr 2024
Published Online:
30 Sep 2024
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1639
Pages:
1637–1651

Abstract

In India Z Atman’s model has very less applicability and untouched in the research area, as this model has highly successful and have more than 85 percent of success rate there is a need to utilize this model for the Indian companies. The present study is about Z Alman’s Score Model applied on four selected Tata Group companies, listed in the NSE for a study period of 2020-2022. Where the study concludes that, among the four selected companies Tata Chemicals which are reported as high financial healthiness with Z score of 2.94 which indicates that the company has strong financial standards and support and there is absolutely no scope for bankruptcy in the near future. Thereafter, Tata Steel company reported Z score of 1.86 which also indicates the company is financially doing well but there is a chance of being bankrupted. So, the company should be cautious about its existing operations and strategies. Thereafter, Tata Power company reported Z score of 1.35 which indicates it is in a very tough position where there is a need to take immediate actions to make sure the company to get it out of that situation as soon as possible. Finally, Tata Motors company reported Z score of 1.69 which indicates that it is in dangerous zone in terms of financial position there should be a huge chance of being bankrupt. So, the company should focus on rebuilding its financial structure in order to overcome the instability and financial distress. Thus, the present study concludes that, among the four companies which are selected among the Tata group three were in the safer position and the only one company was in the danger position due to pandemic affect.

Keywords

Subject Classifications

91B0591G80

References

[1] Fitzpatrick, Matthew & Hargrove, William. Fitzpatrick MC, Hargrove WW. The projection of species distribution of non-analog climate. Biodiv Conserv 18: 2255-2261. Biodiversity and Conservation. 18. 2255-2261 (2009). 10.1007/s10531 models and the problem -009-9584-8.
[2] Hillegeist, S., Keating, E., Cram, D., &Lundstedt, K. Assessing the probability of bankruptcy. Review of Accounting Studies, 9(1), 5-34 (2004).
[3] I wokZ, Iberedem & Okpe, A. A Comparative Study between Univariate and Multivariate Linear Stationary Time Series Models. American Journal of Mathematics and Statistics. 2016. 203-212 (2016). 10.5923/j.ajms.20160605.02.
[4] Mihalovič, Matúš. Performance Comparison of Multiple Discriminant Analysis and Logit Models in Bankruptcy Prediction. Economics & Sociology. 9. 101-118 (2016). 10.14254/2071-789X.2016/9-4/6.
[5] Magundo, Shukurani & Muhua, George & Okuto, Erick.  Multiple Discriminant Analysis As Applied To Language Distinction (2018).
[6] Nomani, A., khan, K., Shaja., S.N., Afzal, M.A., & Salman, mohad.  Financial crisis of Indian sugar industry: Case study of Uttar Pradesh. Journal of Statistics and Management Systems, 25(5), 1303-1317 (2022). https://doi.org/10.1080/09720510.2022. 2092990.
[7] Jelena & Christian. The evaluation of bankruptcy prediction models based on socio-economic costs, Expert Systems with Applications, Volume 227, 1 October 2023, 120275 (2023), https://doi.org/10.1016/j.eswa.2023.120275.
[8] Lennox, Clive S. The Accuracy and Incremental Information Content of Audit Reports in Predicting Bankruptcy. Journal of Business Finance & Accounting 26: 757–78 (1999).
[9] Shin, Kyung Shik, and Yong Joo Lee. A Genetic Algorithm Application in Bankruptcy Prediction Modeling. Expert Systems with Applications 23: 321–28 2002 ().
[10] Barboza, Flavio, Herbert Kimura, and Edward Altman. 2017. Machine Learning Models and Bankruptcy Prediction. Expert Systems with Applications 83: 405–17.
[11] Ghosh,A., &Kapil, S. Is Altman’s Model efficient in predicting bankruptcy? – A comparison among the Altman Z-score, DEA, and ANN models. Journal of Information and Optimization Sciences, 43(6), 1191-1207 (2022), https://doi.org/10.1080/02522667.2022.2117322.
[12] Polemis, D. &Gounopoulos, D. Prediction of distress and identification of potential M&As targets in UK, Managerial Finance, 38(11), 1085 – 1104 (2012). http://dx.doi.org/ 10.1108/03074351211266801.
[13] Pongsatat, S., Ramage, J., & Lawrence, H. Bankruptcy prediction for large and small firms in Asia: a comparison of Ohlson and Altman. Journal of Accounting and Croporate Governance, 1(2), 1-13 (2004).
[14] Muthukumar, G., &Sekar, M. Fiscal Fitness of Select Automobile Companies in India: Application of Z-score and Springate Models. The XIMB Journal of Management, 11(2) (2014).
[15] Etemadi, H., AnvaryRostamy, A., &Dehkordi, H. A genetic programming model for bankruptcy prediction: empirical evidence from Iran. Expert Systems with Applications, 36(2), 3199-3207 (2009).
[16] Charitou, A., Neophytou, E., &Charalambous, C. Predicting corporate failure: empirical evidence for the UK, European Accounting Review, 13(3), 465-497 (2004). http://dx.doi.org/ 10.1080/0963818042000216811
[17] Du Jardin, P., Bankruptcy prediction models: How to choose the most relevant variables? Bankers, Markets & Investors, issue 98, January-February, pp. 39–46 (2009).
[18] Lin,W.Y., & Pan, W.T. A Study of impact from the Hybrid Model combining Z score and GAANFIS on business performance. Journal of Statistics and Management Systems, 11(6), 1195-11206 (2008). https://doi.org/10.1080/09720510.2008.107001367
[19] Gupta,Y.P., Bagchi, P.K., & Rao, R.P. A Comparative analysis of the performance of Alternative Discriminant Procedures: An application to bankruptcy prediction. Journal of information and optimization Sciences, 11(3), 457-471 (1990), http://doi.org/1080/02522667.1990.10699037.
[20] Altman, Edward I. 1968. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance 23: 589–609.

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