Systems of Quantitative Characteristics (Financial, Manufacturing, etc.) Forecasting Based on Machine Learning Approach (Including Artificial Neural Network)

In this work, the methods of real options are considered, with the help of them an assessment and analysis of a project for the development of an oil and gas field is carried out and the dependence of the values ​​of options on changes in forecast prices for fuel resources is examined. The aim of the work is to identify the best model of real options for evaluating a project in the oil and gas industry. The methods of real options are analyzed, the influence of different types of options in combination with each other and the dependence of the forecast on price fluctuations in the fuel market are investigated. It is concluded that the most realistic and high-quality forecasts are obtained using a logarithmic binomial lattice, the hypothesis that the rejection option is most useful in unfavorable market conditions, and the extension option, on the contrary, is favorable, is confirmed. The necessity of a thorough analysis of the project, its indicators, an accurate forecast of fluctuations in the prices of fuel resources and the preparation of a strategy according to which the investor will adhere to a certain scenario and, based on this, choose the right and profitable types of options that will be calculated according to the most efficient method, is justified. The conclusions considered in the article can be used in determining the investment strategy in the oil and gas markets, both from investors and from companies implementing the project in this area, since the results of the development and implementation of options affect the company's reputation, attracting or repelling investors. Thus, with the competent use of such a tool as real options, a competent manager can attract a larger amount of investment than before, allowing you to develop your project even faster and better.