The use of the system dynamics model to determine the probability of company default

This research demonstrates the approach of using the system dynamics model to assess the probability of company default that is a relevant problem in credit risk analysis. System dynamics offers models in which the reality is simulated structurally. According to the principles of system dynamics, the company is represented in the form of continuously interacting elements and external factors. Enterprise dynamics and the enterprise's resistance to various macroeconomic environments are determined by functional dependencies and differential equations that describe the links between the elements of the model. The behavior of random macroeconomic variables is described with a multivariate ARIMA-GARCH model, which is used in econometrics to predict non-stationary time series. The probability of company default is determined as a result of experiments with the obtained system dynamics model using the Monte Carlo simulation. The estimation of a default probability is the overall share of macroeconomic scenarios leading to the ruin of the enterprise. A comparative analysis of the obtained results and data from Moody's and Fitch demonstrates the closeness of the probability of company defaults obtained by simulation and corresponding estimates of rating agencies, which makes it possible to conclude that the considered approach is acceptable for estimating the probability of default of a borrower.