Digital model for investment risk assessment in the energy sector

Purpose. The purpose of the researchis to develop a digital model and design a comprehensive algorithm for assessing investment risk in the energy sector to determine investment efficiency and minimize the risk of bankruptcy when investing with borrowed funds at an interest rate. The methods. From a mathematical perspective, the digital model is based on the application of Chebyshev’sinequality, generalized considering the lognormal distribution of the random variable of investment efficiency. A rigorous mathematical apparatus is used in combination with probabilistic estimates and an asymptotic approach. The numerical analysis of the risk model was carried out using the professional mathematical software Maple 18. Findings. A digital model for investment risk assessment has been created and a comprehensive algorithm for its analysis has been developed, which consists of the following key stages: quantitative assessment of the minimum probability of risk; determination of the limiting value of the loan interest rate under the condition of the minimum probability of risk; evaluation of the range of variation in the mathematical expectation and standard deviation of investment efficiency, where the probability of bankruptcy is minimized; estimation of the range of variation in the standard deviation of investment efficiency and the loan interest rate that minimizes the probability of bankruptcy; numerical and asymptotic determination of the maximum risk.Quantitative estimates of bankruptcy probability have been obtained and graphically illustrated based on variations in the parameters of the lognormal distribution of the random variable of investment efficiency. The originality. A digital model and a comprehensive algorithm for its evaluation have been developed, integrating modern methods of mathematical modelling and digital technologies. Analytical relationships and numerical estimates of risk probability have been obtained, allowing for the minimization of bankruptcy risk under credit investment conditions. Practical implementation. The research results can be used to assess investment risks in real energy sector projects, which will contribute to increasing the efficiency of decision-making regarding investment strategies.