Use of Probabilistic Approaches to Predict Cash Deficits

Abstract

This article deals with issues related to the use of mathematical methods of cash deficit probability predictions. A number of objective and subjective factors are described that prevent the wide integration of mathematical methods in the practical activities of economists. It is justified that, due to the large number of external and internal factors affecting the economic system state, the values of indicators of an economic system state are often random. The possibility of using probability theory methods to predict the occurrence of cash deficits is proved. Using empirical data including the results of thousands of observations, the possibility of using the normal distribution density function for the purpose of predicting insufficient funds for payment is illustrated. The essence of the proposed model is that it contains a prediction of a macrotrend—i.e., the risk of a cash gap—based on high-frequency microlevel data. At the same time, a prediction of the probability of a cash deficit, and not its estimation for a specific date, was made. This is the main difference between the described model and common scoring estimates. This article proposes an approach to estimate the probability of a cash deficit based on data from a specific business entity, rather than aggregated data from other organizations.