The Effect of Earnings Quality on Predicting Bankruptcy by Using Artificial Neural Networks Bita Mashayekhi Hamidreza Ganji (Received: 16/Apr/2014; Accepted: 19/Jun/2014) Abstract Predicting of entities’ going- concern assumption in the future periods is an import More
The Effect of Earnings Quality on Predicting Bankruptcy by Using Artificial Neural Networks Bita Mashayekhi Hamidreza Ganji (Received: 16/Apr/2014; Accepted: 19/Jun/2014) Abstract Predicting of entities’ going- concern assumption in the future periods is an important element in decision-making process of many investors. So, ing the predictor variables have been discussed as a challenging issue in the literature of bankruptcy prediction that accounting earnings & profitability variables have been at the top of these issues. Therefore earnings quality has been one of the important measures in the decision-making process of investors in field of bankruptcy prediction. This study has attempted to compare the prediction power of profitability variables among high quality and low quality earnings of Tehran Stock Exchange(TSE) companies and examine the effect of earnings quality on the efficiency of profitability variables in predicting the bankruptcy. In a sample of TSE companies, using artificial neural networks we find that the predictive accuracy of artificial neural networks for high quality earnings companies is significantly greater than of firms low quality earnings. Key Words: Profitability, Predictability, Earning Quality, Bankruptcy, Artificial Neural Network.
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