Abstract
Economic activity of economic entities is associated with the constant search for effective management solutions: the optimal option for the allocation of resources, promising areas of development, the feasibility of introducing new technologies and developing new markets. Complications of internal and external relationships, the presence of a large number of unpredictable indicators limit the activities of an individual enterprise, do not allow to form an optimal strategy for the development of economic objects without the use of specific management methods and models. The basis for modeling management systems, including modeling of priority areas of agricultural sector, is to build a mathematical model. An adequate mathematical model must take into account the dynamics, stochastic uncertainty and unstructured management processes of economic objects, which is quite difficult to implement. In addition, the task of management and decision-making always contains a group of non-material, qualitative factors that are difficult to formalize, describe in quantitative terms, but which certainly have a decisive influence on the quality of the decision. Such "factors of influence" include the human factor. The result of human behavior can nullify any optimal solution, based on any adequate mathematical model. Accordingly, the mathematical model should also take into account the risk impact of the human factor, in the context of the entire management decision-making process. For management system models, there are a number of unresolved formalization and risk considerations. Mathematical formulation of the problem of optimizing economic risk management, as a rule, begins with the formalization of input parameters, qualitative and quantitative estimates of model variables, selection of mathematical tools. The information base of optimization models is the preliminary analytical and statistical indicators of the dynamics of the studied economic object. The article investigates the stochastic model of economic risk management. The set of implementations of random processes is considered as a limited set of random variables with a Markov property, which formalizes the problem of risk management, as a random process of obtaining the predicted benefit.
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