Designing a Bankruptcy Prediction Model Based on Account, Market and Macroeconomic Variables (Case Study: Cyprus Stock Exchange)

Abstract

The development of the Cyprus Stock Exchange together with the increasing trend of investors’ presence in financing activities has led to the importance of this market. In such circumstances, the first step towards a sustainable development of the Exchange is to support the investors. Risk of bankruptcy for the investee is a major challenge that an inexperienced stock investor encounters. In this study, for predicting bankruptcy, an attempt has been made to design a valid and accurate model that could act as a deterrent to improper stock selection. In most of the previous studies, non-native models have been used to predict bankruptcy in companies. However, the present study has attempted to overcome the shortcomings of the earlier studies through designing an indigenous model based on the data collected from 53 non-financial companies out of 103 listed companies in the Cyprus Stock Market from 2007 to 2012, using a complete set of variables affecting bankruptcy (accounting, market and macroeconomic variables), and with using the logistic regression method. The results showed that the accuracy of bankruptcy models that are based on accounting and market variables has been respectively 91.2% and 82.1%, respectively. On the other hand, it was shown that there is no significant relationship between macroeconomic variables and the probability likelihood of bankruptcy.

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