Year of Graduation
Probability of Default Modeling for Russian Banks
We compare several models for estimating the default probabilities of Russian banks using national statistics from 1998 to 2011, and find that a binary logit regression with a quasi-panel data structure works best. The results indicate that there is a quadratic U-shaped relationship between a bank's capital adequacy ratio and its probability of default. In addition, macroeconomic, institutional, and time factors significantly improve model accuracy. These results are useful for national financial regulatory authorities, as well as for risk-managers in commercial banks.