پيش بيني درماندگي مالي با استفاده از تحليل پوششي داده ها

Financial Distress prediction: A DEA approach

Financial distress has a critical impact on decision making of managers, investors and shareholders. In current financial distress prediction models, various financial ratios are usually selected as prediction variables. But in this paper we propose a financial distress prediction model based on firms efficiency score as variable. In the proposed method, Data Envelopment Analysis (DEA) is employed as a tool to evaluate the firmʹs efficiency score. To verify the model accuracy another model is designed based on Multivariate Discriminant Analysis (MDA) that widely used in literature. Ultimately to investigate the effectiveness of firmʹs efficiency score on financial distress prediction, these scores are entered in an MDA model as one of its variables. The results show that all the three proposed models in this paper, has the ability of predicting financial distress for two years prior to its occurrence. It implies that, DEA efficiency score is an effective predictor variable.