Year of Graduation
Increase of Banks' Credit Risks Forecasting Power by the Usage of the Set of Alternative Models
Financial Markets and Financial Institutions
The paper is aimed to compare divergence of existing models of credit risks and to create a synergic reliable model. For this purpose, it applied Rating model and Probability of Default model to the same dataset and normalised its estimates to the common scale. After thorough analysis of probability density functions of that output, the optimal weights and monotonic transformations were assigned to each model. As a result, the new synergic model with higher forecasting power (predicted 44% of precise estimates) was obtained.