Abstract

The article is devoted to the problems of measuring economic risk on the basis of fuzzy sets. An analysis and further development of the methodical apparatus for quantitative assessment of the degree of economic risk is carried out within the framework of the interpretation of the degree of risk as the degree of possibility of discrepancy between the value of the criterion indicator and its normative level. As a direct subject of consideration, the case is taken when there is a simultaneous fuzziness of assessments of the criterion and the normative. The principal emphasis in the study is made on the computational aspect (computational versions) of the analyzed methods for assessing the degree of economic risk. Initially, one of the existing methods for measuring economic risk is considered, the scope of which is the situation when fuzzy assessments of the criterion economic indicator and its normative imply a horizontal, i.e. by levels of affiliation (alpha-levels) way of presentation. Based on the results of the analysis of expressions that define this method, its modification is proposed, which is based on the alpha-level weighing of its basic structural components. Comprehensive attention in the study is paid to the method of assessing the degree of risk for a fuzzy assessment of a criterion economic indicator in relation to a fuzzy assessment of the normative, which is based on a probabilistic analogy. Within this framework, the formulas that form the computing apparatus of this methodical approach are systematized and supplemented. Among other things, the generalized computational formulas of the commented method have been supplemented. For the conditional situation, on the basis of a series of simulation computations, a comparative analysis of the studied alternative methods of measuring economic risk is carried out. The accomplished analysis made it possible to identify certain regularities of the mutual distribution of values of the degree of risk, obtained when they are applied simultaneously.

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