Altman’s Z-model an approach to predict the financial distress of selected companies of Tata Group in India
*Karthik ReddyCorresponding authormbaskreddy@gmail.comDepartment of Management StudiesNitte Meenakshi Institute of TechnologyBengaluru, Karnataka, 560064, India0000-0002-1810-6570View full profile → , B. Arun Kumar1420arun@gmail.comDepartment of Management StudiesKakaraparti Bhavanarayana CollegeVijayawada, Andhra Pradesh, 520001, India0009-0001-6365-447XView full profile → , V. Shireeshashireeshachakry@gmail.comDepartment of CommerceGovt. City College, NayapulHyderabad, Telangana, 500002, India0009-0001-5177-8010View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 11 Apr 2024
- Published Online:
- 30 Sep 2024
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1639
- Pages:
- 1637–1651
Abstract
Keywords
Subject Classifications
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.




