Corporate financial distress prediction: An application of Multiple Discriminant analysis

Abstract

Recent failures of large corporations at the international level and instability of securities in Sri Lanka have emphasized the importance of evaluating the companies' financial distress. One of the methods of evaluating financial distress is bankruptcy prediction models. They are the tools for measuring the financial healthiness of companies in the future. This research aims to bring out the theoretical foundations and make a deep study about the results of Altman’s model (1968) in the Colombo Stock Exchange through statistical techniques of Multiple Discriminant Analysis and Logistic Regression Model. The data was gathered from 2013 to 2018. The results obtained from the Multiple Discriminant Analysis identified that Altman’s model could predict bankruptcy within one year before with an accuracy rate of 72.10%. According to the logistic regression analysis, Altman’s model has a higher predictability power. This research's findings can be applied by potential investors when designing their investment strategies in healthy financial companies.