Distance to default in banks with the approach of transformed- data maximum likelihood estimate method

We introduced estimation methods include the market value proxy , volatility restriction , KVM , and the transformed-data maximum likelihood with strengths and weaknesses in order to estimate distance to default . If the correct estimation method is not used, there will be distortion in the results . Considering the different balance sheet structure , the transformed- data is introduced by considering the coefficient of other debts as an optimal method in order to estimate distance to default in banks. Then, we used Merton's adjusted model and the transformed- data method during 2012 to 2019 to calculate market value of assets, asset volatility, distance to default, and probability of default in some private banks. The results show that the highest market value of assets is related to Bank Mellat and the lowest is Post Bank . The results achieved by comparing are different regarding volatility of assets, distance to default, and the probability of default. Additionally, the average market value of banks' assets is increasing and the average volatility of assets and the average distance to default is decreasing . In other words, Banks have become closer to default . The Dickey-Fuller test confirms the Stationary of the research model.