Failure prediction from the investors’ view by using financial ratios. Lesson from Romania

Loading...
Thumbnail Image
Date
2016-12-05
Journal Title
Journal ISSN
Volume Title
Publisher
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Abstract
The purpose of our study is to identify which financial indicators have a significant impact on the probability of Romanian companies’ bankruptcy risk from the investors’ point of view by studying the impact on the probability of shares delisting from the stock exchange. The research is conducted on a sample of 16 failed and 21 non-failed non-financial companies listed on the Bucharest Stock Exchange between 2002 and 2012. The Logit analysis is used for identifying the variables that are significant and have predictive power on distress likelihood. By using 12 main financial ratios, we estimate three alternative Logit models for determining their signs, significance, predictive power, efficiency of fit tests. The first model provides the highest explanatory power. Three variables such as Flexibility ratio (FLEX), Assets turnover (ASTU) and Current assets turnover (CASTU) are found to be significant determinants for stock exchange delisting. These three variables provide 52.59% of correct prediction of bankruptcy risk. The percentage for correctly classified observations for the fitted Logit model is of 83.33%. Moreover, this research attempts to reveal the changes that may appear among bankruptcy predictors given that the bankruptcy risk model is developed from the investors’ point of view and not from that of a simple decision-making person. For a stock market investor, bankruptcy already starts at the stage of delisting the company because the investment was strongly compromised, whether or it continues its activity or not. Orientation towards investors when predicting bankruptcy risk is the main element of originality that our research adds to the scientific achievements in bankruptcy, until this moment.
Description
Subject(s)
delisting, failure prediction, financial ratios, Logit model
Citation
ISSN
1212-3609
ISBN
Collections