Purpose: Development of the apparatus of the stochastic processes econometric modeling. Discussion: The authors identify risk component in the dynamics of stochastic processesin the economy. Theoretical justification of the alternative and proportional expectations is usedto make probabilistic nature of the risk. Results: The authors suggest stochastic process decomposition based on econometric approach to allocate a probability space of risks, and to identify shocks realizations that lie beyond the boundary of this space. Proportional expectations hypothesis distinguished two types of the event influence on the stochastic process realization: continuous (risk) and discrete (shock). The authors suggest model errors and residualsas the main source of information for the identification of the probability space of risks. The technique of econometric modeling of the price and return processes on stock market under theconditions of the proposed hypotheses is considered in the empirical part of the study. F-testresults have not disproved the statement that the model residuals provide additional information about the simulated rate in the case of lack of relevant factors.

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This paper proposes a regression-matrix model for predicting the socioeconomic development of regional systems. The ability to build up such a model provides for the classification of indicators into groups depending on their socioeconomic purpose. The structured data presentation has led to the prerequisite for a graded construction of models that ensure a proactive balance of the dynamics at two levels: cluster-type and system-based. According to the assumption, group balance should ensure the consistency of the expected growth of each indicator with the group dynamics of the corresponding block. The systemic balance is provided by the introduction of group dynamics indicators in the form of principal components, in turn, the regression-matrix approach is applied.