This paper explores the prediction of bankruptcy of Greek retail and wholesale trade companies and, in particular, the relation between the forecasting ability of the Logit model and the degree of homogeneity of the samples of bankrupt and healthy companies. A sample of 119 bankrupt companies was matched with an equal sample of healthy companies for the period 2003-2014, based on year, sector, and sub-sector, which was formed by random selection. Using the method of factor analysis, seven financial ratios were selected, which are the independent variables of the model. Applying the Logit model, the results showed a significant explanatory capability of the model in the trade sector as a whole as well as in the wholesale trade sub-sectors, which increases as the homogeneity of samples of bankrupt and healthy companies increases.In particular, the predictive capability of the model that we used improved by 14.3% regarding the classification of bankrupt firms when the same methodology was applied from the broader sector to the sub-sector. Moreover, the independent variable of capital structure has the highest stability and contributes substantially to the discriminant validity of the Logit model.
Key words: Bankruptcy, corporate bankruptcy, sectoral forecasting models, financial and accounting ratios.
Copyright © 2020 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0