Appraising the Use of KMV Model in Predicting Default of Companies Listed in Tehran Stock Exchange

Until now, different models are presented to predict the status of customer’s credit risk and possibility of bankruptcy. It seems necessarry to deploy a model that is not only based on historical data but also uses market data as index of current situation of customers and even their expectations about future status. The purpose of this article is using KMV model to predict bankruptcy of legal clients of Iranian banks, and to evaluate accurancy of model too. Data have been extracted from a sample of 40 public companies receiving loans from Iranian banks in the years between 1386 and 1387 (h.sh.). This study is practical and uses a quantitative method. It has been observed that KMV model has the capability of predicting default, and discriminates between healthy and unhealthy companies. The model also can predict default of legal clients who receive loans from Iranian banks.