Abstract
Qualitative and quantitative methods of risk assessment of enterprise investment projects and features of their use are considered. A brief overview of modern risk assessment methods is presented, their advantages and disadvantages are indicated. Disadvantages of existing methods include the need for large volumes of reliable source information over a long period of time (statistical method); difficulties regarding the laws of distribution of the studied parameters (factors) and resulting indicators (statistical method, simulation modeling); isolated consideration of a change in one factor without taking into account the influence of others (sensitivity analysis, stability testing method). Fuzzy logic methods are not devoid of subjectivity in assessing the degree of acceptance of a particular consequence caused by the appearance and intensity of prerequisite factors.
 The value of the elasticity coefficient for the indicators of the investment project was studied and those that require increased attention during the implementation of the investment project in order to reduce the level of risk were determined. The need to use the method of sensitivity analysis of performance indicators in the process of implementation of the investment project to assess risk in order to reduce its level and minimize or avoid it is justified. losses, which allows you to determine the most risky initial factors of the project, which contribute to an increase in risk, and therefore negatively affect the final results of its implementation (NPV), and methods of fuzzy logic, which make it possible to combine qualitative and quantitative methods of assessing the risks of capital investments and contribute to the justification of expected loss of cash flows, despite doubts about the effects of various destabilizing factors of the mega, macro- and microeconomic environment. The author's methodical approach to assessing the loss of cash flows from capital investments in the conditions of hostilities in certain regions of Ukraine is proposed. The basis of the developed approach is the elements of the theory of fuzzy sets, in particular operations on fuzzy relations.
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