REASSESSMENT OF CORPORATE BANKRUPTCY PREDICTION MODELS EFFICIENCY: EVIDENCE FROM SERBIA

Vule Mizdraković, Milena Bokić

Abstract


Having in mind various negative influences that corporate bankruptcy has on the economy of the Republic of Serbia, corporate bankruptcy prediction is of extreme importance. Therefore, the basic motive for writing this paper was an attempt to assess the possibility of forecasting bankruptcy of business entities which operate on the Republic of Serbia's market. We have calculated the already formed M-score, formed based on the data from the financial statements of Serbian business entities. As a comparison models, we have calculated the two most acknowledged Z-score models. The randomly chosen sample consisted of 35 entities in bankruptcy and the same number of non-bankrupt entities. The goal of the research was to reassess the relevance of the tested models for a longer period, as well as their precision in the corporate bankruptcy prediction in an unstable economic environment of the Republic of Serbia. According to the results, the conclusion is that the tested M-score proved its precision in bankruptcy prediction in Serbia, and its use is, therefore, recommended. On the other hand, the Altman’s Z-score models do not have statistical relevance and hence we recommend that their use for bankruptcy prediction in the Republic of Serbia should be with caution.

Full Text:

PDF

References


Altman, E. (1968). Financial Ratio, Discriminate Analysis and Prediction of Corporate Bankruptcy. Journal of Finance, 23 (4), pp. 589‒629.

Altman, E., Danovi, A., & Falini, A. (2013). Z-Score Models' Application to Italian Companies Subject to Extraordinary Administration. Journal of Applied Science, 23 (1), pp. 128‒137.

Altman, E., Iwanicz-Drozdowska, M., Laitinen, E., & Suvas, A. (2014, July 9). Distressed Firm and Bankruptcy Prediction in an International Context: A Review and Empirical Analysis of Altman’s Z-Score Model. Retrieved July 1, 2015, from New York University: http://people.stern.nyu.edu/ealtman/IRMC2014ZMODELpaper1.pdf

Bandyopadhyay, A. (2006). Predicting Probability of Default of Indian Corporate Bonds: Logistic and Z-score Model Approaches. The Journal of Risk Finance, 7 (3), pp. 255‒272.

Bankruptcy Supervision Agency. (2015, April 4). Overview of Corporate Bankruptcy Proceedings per Courts. Retrieved April 9, 2015, from Bankruptcy Supervision Agency: http://www.alsu.gov.rs/bap/upload/documents/statistika/BrojPredmeta_Po_Sudovima.pdf

Bauer, J., & Agarwal, V. (2014). Are Hazard Models Superior to Traditional Bankruptcy Prediction Approaches? A Comprehensive Test. Journal of Banking & Finance, 40 (1), pp. 432‒442.

Beaver, W. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4 (1), pp. 71‒111.

Belak, V., & Alijanovic-Barac, Z. (2008). Secrets of the Stock Market. Zagreb: Belak Excellens.

Bellovary, J., Giacomino, D., & Akers, M. (2007). A Review of Bankruptcy Prediction Studies: 1930-Present. Journal of Financial Education, 33 (1), pp. 1‒42.

Chava, S., & Jarrow, R. (2004). Bankruptcy Prediction with Industry Effects. Review of Finance, 8 (4), pp. 537‒569.

Coface. (2013, Spring). Insolvency Report in Central Europe. Retrieved April 09, 2015, from Financialrul: http://www.financiarul.ro/wp-content/uploads/Insolvente_Europa_Centrala_mai_2013_EN.pdf

FitzPatrick, P. (1932). A Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Companies. The Certified Public Accountant, pp. 598‒605.

Giordani, P., Jacobson, T., Schedvin, E., & Villani, M. (2014). Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios. Journal of Financial and Quantitative Analysis, 49 (4), pp. 1071–1099.

Gunathilaka, C. (2014). Financial Distress Prediction: A Comparative Study of Solvency Test and Z-Score Models with Reference to Sri Lanka. IUP Journal of Financial Risk Management, 11 (3), pp. 39‒51.

Hals, T. (2015, April 14). U.S Public Companies Seek Bankruptcy at Fastest First-quarter Rate Since 2010. Retrieved August 13, 2015, from Reuters: http://www.reuters.com/article/2015/04/14/us-usa-bankruptcy-increase-insight-idUSKBN0N528K20150414

Jackendoff, N. (1962). A Study of Published Industry Financial and Operating Ratios. Philadelphia: Temple University, Bureau of Economic and Business Research.

Knezevic, G., Stanisic, N., & Mizdrakovic, V. (2014). Predictive Ability of the Business Excellence Model: The Case of Foreign Investors in Serbia from 2008 to 2012. Teme, 38 (4), pp. 1475‒1488.

Merwin, C. (1942). Financing Small Corporations in Five Manufacturing Industries, 1926-1936. New York: National Bureau of Economic Research.

Mizdraković, V. (2012). Comparative analysis of economic aspects of bankruptcy. Retrieved December 25, 2013, from Singipeda: http://www.singipedia.com/content/3276-Komparativna-analiza-ekonomskih-aspekata-ste%C4%8Daja

Muminovic, S. (2013). Revaluation and Altman`s Z-score – the Case of the Serbian Capital Market. International Journal of Finance and Accounting 2013, 2(1), 13‒18.

Muminovic, S., Pavlovic, V., & Cvijanovic, J. (2011). Predictive Ability of Various Bankruptcy Prediction Z-Score Models for Serbian Publicly Listed Companies. Industry, 39 (3), 1‒12.

Pavlović, V., Muminović, S., & Cvijanović, J. (2011). The adequacy of Taffler’s model for Bankruptcy Prediction of Serbian companies . Industry, 39 (4), pp. 57–70.

Samarakoon, P., & Hasan, T. (2003). Altman’s Z-Score Models of Predicting Corporate Distress: Evidence from the Emerging Sri Lankan Stock Market. The Journal of the Academy of Finance, 1 (1), pp. 119‒125.

Smith, R., & Winakor, A. (1935). Changes in Financial Structure of Unsuccessful Industrial Corporations. Bureau of Business Research, Bulletin No. 51, pp. 3‒44.

Stanisic, N., Mizdrakovic, V., & Knezevic, G. (2013). Corporate Bankruptcy Prediction in the Republic of Serbia. Industry, 41 (4), pp. 145‒159.

Todorovic, M., & Pantelic, M. (2014). From Traditional to Modern Financial Reporting - What is the Price of Modernization. Teme, 38 (4), pp.1559‒1572.


Refbacks

  • There are currently no refbacks.


Print ISSN: 0353-7919
Online ISSN: 1820-7804