An alternative model practice for the results of sovereign risk rating approaches

The importance of global financial markets in the world economy is increasing day by day. So that, market participants need easy to understand and comprehensive information while making investment decisions. Sovereign credit ratings provide transfer of information between market participants via understandable and standardized symbols. Sovereign credit ratings are also a determining factor for financial investment decisions to be made in a country. In this study, sovereign credit rating methods were examined and in addition a new model was proposed. Within the scope of the study, data of balance of payments, local economy, foreign economy, financial sector, income and population, and public finance which can affect the credibility of the country were analyzed and included in the analysis. As a result of the study, a model was developed that measures the probability of default of the countries and expresses this with 21 letter symbolism. Logistic regression method was used in the study and analysis was performed for 115 countries between the years 2008-2017. In this model, weight of public finance and balance of payments modules is 25%, weight of financial sector modüle is 20%, income and population modüle is 17%, and 16% for the foreign economy module. The model output produced in the study and the sovereign ratings of a credit rating agency are compared for the sample countries, and the fundemental methodology approaches between models are shown.