Predicting Corporate Financial Distress in Sri Lanka: An Extension to Z-Score Model

K.G.M. Nanayakkara, A.A. Azeez


The main purpose of this study is to develop a better financial distress prediction model for the Sri Lankan companies using the Z-score model. Fourteen variables have been selected consisting of accounting, cash flow and market based variables. Multivariate Discriminate Analysis (MDA) was used as the analytical technique and stepwise method was used to select the variables with the best discriminating power to a dataset of sixty-seven matched pairs of failed and non-failed quoted public companies over the period 2002 to 2011. The final models are validated using the cross validation method. The results indicate that a model with four predictors of earnings before interest and taxes, cash flow from operations to total debts, retained earnings to total assets, and firm size have achieved the classification accuracy of 85.8% in one year prior to the distress with a very low type I error. Moreover, the model has correctly classified the cases by 79.9% and 69.4% in two year and three year prior to distress respectively. The study has further revealed that the companies with negative cutoff value fall into distress zone while the companies with positive cutoff values fall into safety area. Hence, the study concluded that the companies with cutoff values approximately zero should be considered on mitigating actions for financial distress not only on the accounting information but also on the cash flow and market data.


Financial distress, market variables, multivariate discriminant analysis, Z-Score.

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