Journal of Commerce and Accounting Research

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Applicability of Altman Z-Score In Bankruptcy Prediction of BSE PSUs


Affiliations
1 Department of Business Administration, Manipal University Jaipur, Rajasthan, India
     

   Subscribe/Renew Journal


Prediction of bankruptcy is a critical task. Firms can be hedged from bankruptcy situation by solvency recognition at inceptive stage which may avoid enormity in the near prospective. There are lots of techniques available for measuring the financial health of a business firm wherein Altman’s Z-score is one of the prominent measures for predicting bankruptcy. The study is based on the fundamentals of the companies using financial ratios by taking companies of PSU index listed on Bombay Stock Exchange across different sectors over a period of 6 years from 2013-2018. The finding reveals that Altman’s Z-score model has a remarkable degree of accuracy in predicting distress using financial ratios. The results may be useful for the managers for financial decision making, the stakeholders to choose investment options & others to look after their interest in the concerned manufacturing and non-manufacturing companies.

Keywords

Bankruptcy Projection, Financial Competence, Altman Z-score Model, Financial Distress.
Subscription Login to verify subscription
User
Notifications
Font Size


  • Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.

  • Bandyopadhyay, A. (2006). Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches. The Journal of Risk Finance, 7(3), 255-272.

  • Bardia, S. C. (2012). Predicting financial distress and evaluating long-term solvency: An Empirical study. IUP Journal of Accounting Research & Audit Practices, 11(1).

  • Bwisa, A. S. (2010). Evaluation of applicability of Altman’s revised model in prediction of financial distress in Kenya. Unpublished MBA project. University of Nairobi.

  • Chea, I. D. (2012). The role of cash flow information in predicting financial distress among commercial banks in Kenya. (Unpublished MBA project). University of Nairobi.

  • Wang, Y., & Campbell, M. (2010). Business failure prediction for publicly listed companies in China. Journal of Business and Management, 16(1), 75.

  • Casey, C. J., Bibeault, D., & Altman, E. I. (1984). Corporate financial distress: A Complete guide to Predicting, Avoiding, and Dealing with Bankruptcy. Journal of Business Strategy (pre-1986), 5(000001), 102.

  • Das, K. C. (2012). Banking sector reform and insolvency risk of commercial banks in India. IUP Journal of Applied Finance, 18(1).

  • Eidleman, G. J. (1995). Z scores-A guide to failure prediction. The CPA Journal, 65(2), 52.

  • Gunathilaka, C. (2014). Financial distress prediction: A comparative study of solvency test and Z-Score models with reference to Sri Lanka. The IUP Journal of Financial Risk Management, 39-51.

  • Harrington, W. M. (2009). A timely new study of bankruptcy prediction models from morningstar. Business Valuation Update, 1-6.

  • Crăciun, M., Bucerzan, D., Raţiu, C., & Manolescu, A. (2013). Actuality of bankruptcy prediction models used in decision support system. International Journal of Computers Communications & Control, 8(3), 375-383.

  • Machek, O. (2014). Long-term predictive ability of bankruptcy models in the Czech Republic: Evidence from 2007-2012. Central European Business Review, 3(2), 14.

  • Aneja, R., & Makkar, A. (2013). A comparative study of book value Insolvency of Indian commercial banks: An Application of Z-Score Model. IUP Journal of Financial Risk Management, 10(2).

  • Mohammed, S. (2016). Bankruptcy prediction by using the Altman Z-score model in Oman: A case study of Raysut cement company SAOG and its subsidiaries. Australasian Accounting, Business and Finance Journal, 10(4), 70-80.

  • Murari, K. (2012). Insolvency Risk and Z-Index for Indian Banks: A Probabilistic Interpretation of Bankruptcy. The IUP Journal of Bank Management, 11(3), 7–21.

  • Narendar, V., & Rao, G. A. (2013). Analysis of bankruptcy prediction models and their effectiveness: An Indian perspective. Great Lakes Herald, 3-17.

  • Pam, W. B. (2013). Discriminant analysis and the prediction of corporate bankruptcy in the banking sector of Nigeria. International journal of finance and accounting, 2(6), 319-325.

  • Pradhan, R., Pathak, K. K., & Singh, P. (2011). Z score reveals credit capacity: A Case study of SBI. International Journal of Financial Management, 1(3), 72.

  • Sajjan, R. (2016). Predicting bankruptcy of selected firms by applying Altman’s z-score model. International Journal of Research–Granthaalayah, 4(4), 152-158.

  • Sembiring, T. M. (2015). Bankruptcy prediction analysis of manufacturing companies listed in Indonesia stock exchange. International Journal of Economics and Financial Issues, 5(1S), 354-359.

  • Shappell, B. (2012). Old model, new tricks Z-score innovator and credit congress speaker rolls out latest vision for bankruptcy predictor. Business Credit, 4-6.

  • Strobel, F. (2011). Bank insolvency risk and different approaches to aggregate Z-score measures: a note. Applied Economics Letters, 18(16), 1541-1543.

  • Strobel, F. (2011). Bank insolvency risk and Z-score measures with unimodal returns. Applied Economics Letters, 18(17), 1683-1685.

  • Sofat, R., & Hiro, P. (2015). Strategic financial management (2nd ed.). Phi Learning Pvt. Ltd. ISBN: 9788120351608.

  • Bellovary, J. L., Giacomino, D. E., & Akers, M. D. (2007). A review of bankruptcy prediction studies: 1930 to present. Journal of Financial education, 1-42.

  • Hayes, S. K., Hodge, K. A., & Hughes, L. W. (2010). A study of the efficacy of Altman’s Z to predict bankruptcy of specialty retail firms doing business in contemporary times. Economics & Business Journal: Inquiries & Perspectives, 3(1), 130-134.

  • Hull, J. (2012). Risk management and financial institutions, + web site (Vol. 733). John Wiley & Sons.

  • O’Leary, E. G. (2001). Business failure prediction and the efficient market hypothesis. Unpublished MBA Research Project, Simon Fraser University, November.

  • Beaver, W. H. (1968). Market prices, financial ratios, and the prediction of failure. Journal of Accounting Research, 179-192.

  • Bilanas, A. F., & Harris, F. (2004). A methodology predicting failure in the construction Industry. Journal of Construction Management and Economics, 13(3), 189-196.

  • Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.

  • Bryant, S. M. (1997). A case-based reasoning approach to bankruptcy prediction modeling. Intelligent Systems in Accounting, Finance & Management, 6(3), 195-214.

  • Carrol, P., & Nelson, R. T. (2008). How to recognize and avoid organizations′ decline. Sloan Management Review, No. Spring, 41-46.

  • Chan, J. K., Tam, C. M., & Cheung, R. K. (2005). Construction firms at the crossroads in Hong Kong: Going insolvency or seeking opportunity. Engineering, Construction and Architectural Management, 12(2), 111-124.

  • Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 109-131.

  • Rao, N. V., Atmanathan, G., Shankar, M., & Ramesh, S. (2013). Analysis of Bankruptcy prediction models and their effectiveness: An Indian perspective. Great Lakes Herald, 7(2), 3-17.

  • Rao, N. V., Atmanathan, G., Shankar, M., & Ramesh, S. (2013). Analysis of bankruptcy prediction models and their effectiveness: An Indian perspective. Gt. Lakes Her, 7(2).

  • Malik, M. S., Awais, M., Timsal, A., & Hayat, F. (n.d.). Z-Score Model: Analysis and Implication on Textile Sector of Pakistan. International Journal of Academic Research, 4(2), 140-158.

  • Abdullah, M. (2015). An empirical analysis of liquidity, Profitability and Solvency of Bangladeshi Banks.

  • Muthukumar, G. (2014). Fiscal fitness of select automobile companies in India: Application of Z-score and springate Models. Vilakshan: The XIMB Journal of Management, 11(2).

  • Gowri, M., & Sekar, M. (2014). Assessing the financial health of select automobile companies in India: A quantitative approach using the Z-Score multi-discriminant financial analysis model. Great Lakes Herald, March, 8(1), 32-45.

  • Al-Dalayeen, B. O. (2016). Evaluating the financial health of jordan International investment company limited using Altman’s Z-Score model. International Journal of Applied, 6(3).

  • Swalih, M. M., & Vinod, M. S. (2017). Application of Altman Z Score on BSE-Greenex companies. Journal of Applied Management and Investments, 6(3), 205-215.

  • Singh, D. (2013). Applications of Z-Score model to predict financial health in selected real estate companies listed in NSE (for the Period 2007-2011).

  • Lakshmi, K. B., Saraswathi, S., & Ramakrishna, Y. An empirical analysis on effect of IPO’s on long run stock performance of selected listed companies in the National Stock Exchange of India.

  • Nyanga, M. (2018). An evaluation of financial distress and its antecedents in public sugar companies in kenya (doctoral dissertation, kenyatta university).

  • Chowdri, (G. P.). Performance of automobile sector- A study of selected stocks of two-wheeler manufacturing companies in India.

  • Ahmad, I. (2016). A study of financial performance of Hindustan petroleum corporation limited since 2000 (Doctoral dissertation, Aligarh Muslim University).

  • Praveena, S. (2013). An empirical analysis of financial efficiency and stock returns of sugar industry in India (doctoral dissertation, Tamil Nadu agricultural university Coimbatore).

  • Chotalia, P. (2012). Evaluation of financial health of sampled private sector banks with Altman Z-score model. Circulation in more than 85 countries, 7.

  • Manousaridis, C. O. (2017). Z-Altman’s model effectiveness in bank failure prediction - The case of European banks. Master thesis.

  • Pradhan, R. (2011). Prediction of Z-Score for private sector banking firms. International Referred Research Journal, 94-98.

  • Awais, M., Hayat, F., Mehar, N., & Waqar-ul-Hassan. (2015). Do Z-Score and current ratio have ability to predict bankruptcy? Developing Country Studies, 30-36.


Abstract Views: 309

PDF Views: 0




  • Applicability of Altman Z-Score In Bankruptcy Prediction of BSE PSUs

Abstract Views: 309  |  PDF Views: 0

Authors

Arpita Agarwal
Department of Business Administration, Manipal University Jaipur, Rajasthan, India
Ity Patni
Department of Business Administration, Manipal University Jaipur, Rajasthan, India

Abstract


Prediction of bankruptcy is a critical task. Firms can be hedged from bankruptcy situation by solvency recognition at inceptive stage which may avoid enormity in the near prospective. There are lots of techniques available for measuring the financial health of a business firm wherein Altman’s Z-score is one of the prominent measures for predicting bankruptcy. The study is based on the fundamentals of the companies using financial ratios by taking companies of PSU index listed on Bombay Stock Exchange across different sectors over a period of 6 years from 2013-2018. The finding reveals that Altman’s Z-score model has a remarkable degree of accuracy in predicting distress using financial ratios. The results may be useful for the managers for financial decision making, the stakeholders to choose investment options & others to look after their interest in the concerned manufacturing and non-manufacturing companies.

Keywords


Bankruptcy Projection, Financial Competence, Altman Z-score Model, Financial Distress.

References