A Review of Financial Distress Prediction Models: Logistic Regression and Multivariate Discriminant Analysis
DOI:
https://doi.org/10.52962/ipjaf.2017.1.3.15Keywords:
Financial Distress Prediction, Logistic Regression, Multivariate Discriminant Analysis, BankruptcyAbstract
In corporate finance, the early prediction of financial distress is considered more important as another occurrence of business risks. The study presents a review of literature for early prediction of financial bankruptcy. It contributes to the formation of a systematic review of the literature regarding previous studies done in the field of bankruptcy. It addresses two most commonly used financial distress prediction models, i.e. multivariate discriminant analysis and logit. Models are discussed with their advantages and disadvantages. After methodological review, it seems that logit regression model (LRM) is more advantageous than multivariate discriminant analysis (MDA) for better prediction of financial bankruptcy. However, accurate prediction of bankruptcy is beneficial to improve the regulation of companies, to form policies for companies and to take any precautionary measures if any crisis is about to come in future.
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Abdullah, N. A. H., Halim, A., Ahmad, H., & Rus, R. M. (2008). Predicting corporate failure of Malaysia’s listed companies: Comparing multiple discriminant analysis, logistic regression and the hazard model. International Research Journal of Finance and Economics, 15, 201-217.
Agarwal, V., & Taffler, R. (2008). Comparing the performance of market-based and accounting-based bankruptcy prediction models. Journal of Banking & Finance, 32(8), 1541-1551.
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
Altman, E. I., & Narayanan, P. (1997). An international survey of business failure classification models. Financial Markets, Institutions & Instruments, 6(2), 1-57.
Altman, E. I., Eom, Y. H., & Kim, D. W. (1995). Failure prediction: evidence from Korea. Journal of International Financial Management & Accounting, 6(3), 230-249.
Altman, E. I., Haldeman, R. G., & Narayanan, P. (1977). Zeta TM analysis a new model to identify bankruptcy risk of corporations. Journal of Banking & Finance, 1(1), 29-54.
Argenti, J. (1976). Corporate collapse: the causes and symptoms. McGraw-Hill London.
Aziz, A. M., & Dar, H. A. (2006). Predicting corporate bankruptcy: where we stand?. Corporate Governance: The international journal of business in society, 6(1), 18-33.
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.
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of accounting research, 4(1), 71-111.
Beaver, W. H., McNichols, M. F., & Rhie, J. (2005). Have financial statements become less informative? Evidence from the ability of financial ratios to predict bankruptcy. Review of Accounting Studies, 10(1), 93-122.
Begley, J., Ming, J., & Watts, S. (1996). Bankruptcy classification errors in the 1980s: An empirical analysis of Altman's and Ohlson's models. Review of Accounting Studies, 1(4), 267-284.
Bhunia, A., & Sarkar, R. (2011). A study of financial distress based on MDA. Journal of Management Research, 3(2), 1.
Bidin, A. R. (1988). The development of a predictive model (PNBScore) for evaluating the performance of companies owned by the government of Malaysia. Studies in Banking & Finance, 7, 91-103.
Blum, M. P. (1974). Failing Company Discriminant Analysis, Journal of Accounting Research,12 (1): 1-25.
Campbell, J. Y., Hilscher, J., & Szilagyi, J. (2008). In search of distress risk. The Journal of Finance, 63(6), 2899-2939.
Canbas, S., Cabuk, A., & Kilic, S. B. (2005). Prediction of commercial bank failure via multivariate statistical analysis of financial structures: The Turkish case. European Journal of Operational Research, 166(2), 528-546.
Chava, S., & Jarrow, R. A. (2004). Bankruptcy prediction with industry effects. Review of Finance, 8(4), 537-569.
Chen, M. Y. (2011). Predicting corporate financial distress based on integration of decision tree classification and logistic regression. Expert Systems with Applications, 38(9), 11261-11272.
Deakin, E. B. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting Research, 10 (1), 167-179.
Dutta, A., Bandopadhyay, G., & Sengupta, S. (2015). Prediction of stock performance in Indian stock market using logistic regression. International Journal of Business and Information, 7(1), 105-134.
Eisenbeis, R. A. (1977). Pitfalls in the application of discriminant analysis in business, finance, and economics. The Journal of Finance, 32(3), 875-900.
Etemadi, H., Rostamy, A. A. A., & Dehkordi, H. F. (2009). A genetic programming model for bankruptcy prediction: Empirical evidence from Iran. Expert Systems with Applications, 36(2), 3199-3207.
Geng, R., Bose, I., & Chen, X. (2015). Prediction of financial distress: An empirical study of listed Chinese companies using data mining. European Journal of Operational Research, 241(1), 236-247.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis. Uppersaddle River. Multivariate Data Analysis (5th ed) Upper Saddle River.
Her, Y. W., & Choe, C. (1999). A comparative study of Australian and Korean accounting data in business failure prediction models. Melbourne: La Trobe University.
Hillegeist, S. A., Keating, E. K., Cram, D. P., &Lundstedt, K. G. (2004). Assessing the probability of bankruptcy. Review of Accounting Studies, 9(1), 5-34.
Jones, S., & Hensher, D. A. (2004). Predicting firm financial distress: A mixed logit model. The Accounting Review, 79(4), 1011-1038.
Kolari, J., Glennon, D., Shin, H., & Caputo, M. (2002). Predicting large US commercial bank failures. Journal of Economics and Business, 54(4), 361-387.
Laitinen, E. K., Lukason, O., & Suvas, A. (2014). Behaviour of financial ratios in firm failure process: an international comparison. International journal of finance and accounting, 3(2), 122-131.
Lee, S., Ryu, J. H., & Kim, I. S. (2007). Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: a case study of Youngin, Korea. Landslides, 4(4), 327-338.
Lennox, C. (1999). Identifying failing companies: a re-evaluation of the logit, probit and DA approaches. Journal of Economics and Business, 51(4), 347-364.
Li, H., Lee, Y., Zhou, Y., & Sun, J. (2011). The random subspace binary logit (RSBL) model for bankruptcy prediction. Knowledge-Based Systems, 24(8), 1380-1388.
Micha, B. (1984). Analysis of business failures in France. Journal of Banking & Finance, 8(2), 281-291.
Mihalovic, M. (2016). Performance comparison of multiple discriminant analysis and logit models in bankruptcy prediction. Economics & Sociology, 9(4), 101.
Nam, J. H., & Jinn, T. (2000). Bankruptcy prediction: Evidence from Korean listed companies during the IMF crisis. Journal of International Financial Management & Accounting, 11(3), 178-197.
Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of accounting research, 18(1), 109-131.
Premachandra, I. M., Bhabra, G. S., & Sueyoshi, T. (2009). DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique. European Journal of Operational Research, 193(2), 412-424.
Rashid, A., & Abbas, Q. (2011). Predicting Bankruptcy in Pakistan. Theoretical and Applied Economics, 18(9), 103–128.
Sarlija, N., Penavin, S., & Harc, M. (2009). Forecasting enterprise illiquidity in Croatia. Zbornik Ekonomskog fakulteta u Zagrebu, 7(2), 21-36.
Shumway, T. (2001). Forecasting bankruptcy more accurately: A simple hazard model. The Journal of Business, 74(1), 101-124.
Tabachnick, B. G. & Fidell, LS (2001). Using multivariate statistics. Boston: Allyn and Bacon. Bamberger et, 31, l.
Ugurlu, M., & Aksoy, H. (2006). Prediction of corporate financial distress in an emerging market: the case of Turkey. Cross-Cultural Management: An International Journal, 13(4), 277-295.
Zavgren, C. V. (1985). Assessing the vulnerability to failure of American industrial firms: a logistic analysis. Journal of Business Finance & Accounting, 12(1), 19-45.
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