Abstract
This article is dedicated to the theoretical study of applying the Monte Carlo method for evaluating the efficiency of investment projects within enterprises. The author examines the principles and advantages of using this stochastic method in modeling economic parameters and project risks, as well as analyzing the method's capabilities in generating various scenarios for justifying investment decisions based on probabilistic calculations. The article explores methodological aspects of simulation modeling of investments, including the creation of applied mathematical models that simulation real economic processes and situations using pseudorandom numbers to generate random variables. This allows for the determination of potential financial outcomes of investment projects with varying degrees of risk and uncertainty. The historical development of the Monte Carlo method and its contemporary use in investment analysis are highlighted, emphasizing its significance in providing a deep understanding of variations in the initial data of investment projects. Particular attention is paid to the method's ability to adapt and account for uncertainty in complex investment scenarios, making it an indispensable tool for investment analysis. Efficiency indicators of investment projects, which are used to assess the economic benefits of investments, are analyzed. Key indicators include Net Present Value (NPV), Internal Rate of Return (IRR), and Profitability Index (PI). The Monte Carlo method is used to model the probabilities of various financial scenarios and influences the assessment of these indicators, providing a more detailed analysis of potential risks and returns from projects. The article emphasizes the importance of the Monte Carlo method as a foundation for developing new approaches to evaluating investment projects and managing risks. This contributes to a better understanding of how modern approaches to simulation modeling can affect the decisions of investors and managers, especially in situations where classical evaluation methods may be ineffective. Therefore, the application of the Monte Carlo method in modeling investment projects not only helps assess overall efficiency indicators but also allows for a detailed analysis of potential investment project risks, making it an indispensable tool in contemporary investment analysis.
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