Improvement of the quality of calculations using the Monte Carlo simulation method in the evaluation of mining investment projects

Objectives. The article proposes a modification of the method for quantitative risk assessment (the Monte Carlo simulation method) by taking into account the multifactorial relationship between the key parameters and the risk factors of the investment project, which makes it possible to obtain a more relevant and efficient sample of simulations. Methods. Investigations described in the article are based on statistic and other kind of information of russian gold mining company called Polymetal Ltd. Findings/Improvements. At the moment, the culture of risk management is poorly developed at domestic enterprises, in particular, the risk assessment of new investment projects often boils down to only a small standard classification and identification of some risks and an analysis of the sensitivity of the net present project income to a change in some key indicators. Since the change in parameters occurs without taking into account the objectively existing relationships between them (both in sensitivity analysis and in simulation analysis), the result is biased. Therefore, after doing several thousand iterations, you can get the necessary number of different scenarios with changed key parameters with predefined probability distributions. Further, having constructed a matrix or a scheme of key parameters, it is necessary to determine the relationships between these parameters (based on expert experience, statistical data or from the NPV model), the relationships between the parameters are determined. After that, those scenarios are excluded from the sample, the key parameters of which do not correspond to certain dependencies among themselves. Thus, we increase the objectivity of imitation scenarios of the NPV investment project. Application: The investigation results can be used by Russian mining companies to improve the quality of risk managing in mining projects.