Modeling of the Synthetic Credit Rating of Companies

This work is devoted to modeling the scale of the synthetic credit rating to assess the spread of corporate default of Russian companies. Within the framework of the theoretical part of this work, the method of determining the cost of borrowed capital using models for assessing the creditworthiness of companies was studied. Factors reflecting the magnitude of the default risk of companies were identified. The empirical part of the study is divided into 3 main stages. Within the first stage of the work, 5 regression models were constructed, including combinations of several financial ratios and coefficients of the company's organizational structure, reflecting the magnitude of default risk. The second stage of the research is aimed at modeling 5 scales of synthetic credit rating based on the constructed regression models. In the third stage, the developed models were tested for other actual data (out-of-sample method) and the model with the greatest predicted accuracy was identified. This model includes 4 main financial ratios: financial leverage, company development prospects, absolute liquidity ratio and change in the asset turnover ratio for the year. The practical significance of the research is that based on the results obtained, it is possible to determine the risk group for a specific bond and the company as a whole, and also to simulate the spread of corporate default. Moreover, the results of this work can have practical value for potential creditors, investors of the company, as well as the company itself, which must assess its own default risk. Moreover, this model allows us to predict the forecast value for bonds that are being prepared for issue, estimate the real value of bonds for circulation, and simulate the value of a potential loan.