Modelling Optimal Capital Structure in Gas and Oil Sector by Applying Simulation Theory and Programming Language of Python (Qatar Gas Transport Company)

Andrey Kulikov (), Naief Alabed Alkader, Galina Panaedova, Aleksandr Ogorodnikov and Evgenii Rebeka
Additional contact information
Andrey Kulikov: Department of Organization of Medical Provision and Pharmacoeconomics, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
Naief Alabed Alkader: Department of Sustainable Development Finance, Plekhanov Russian University of Economics, 117997 Moscow, Russia
Galina Panaedova: Department of Tax Policy and Customs Affairs, North-Caucasus Federal University, 355017 Stavropol, Russia
Aleksandr Ogorodnikov: Department of Philosophy and Sociology, Kutafin Moscow State Law University (MSAL), 125993 Moscow, Russia
Evgenii Rebeka: Department of Sustainable Development Finance, Plekhanov Russian University of Economics, 117997 Moscow, Russia

Energies, 2023, vol. 16, issue 10, 1-15

Abstract: The goal of this study is to optimize a company’s capital structure by modelling and programming the required equations in the components of weighted average cost of capital. This process will be carried out in the programming language Python, and then Monte Carlo simulation will be applied to increase the number of combinations of debt and equity in the capital structure and obtain more accurate results on the Qatar gas transport company. Throughout various scenarios and outcomes, the study seeks to determine the ideal capital structure that reduces both the firm’s weighted average cost of capital and the risk to which the Qatar gas transport company will be exposed. The suggested method offers a practical instrument for managers and investors to make well-informed decisions when they apply financial strategies to optimize the company’s financial performance. Debt and equity are considered the main parts in the capital structure in every company, and if we can solve the problems connected to these two parts, we can optimize performance. The code of the programming language (Python) used in this study depends on logical discussion to compare different results. This research also will pay attention to the whole probabilities of debt and equity ratios in the Qatar Gas Transport Company. This research considers more variables in the analysis to obtain more accurate results about the firm’s financial status. The results in this research show that the cost of capital in the Qatar Gas Transport Company will be reduced to 5% (currently 6%) if the percentage of debt and equity in the capital structure is changed to 79% and 21%, respectively. In comparison with the other 9999 components of capital structure, this ratio (79%, 21%) will be the optimal one. The scatterplot reflects that the more repeated values of weighted average cost of capital were located around the value of 5%. This fact can enable us to conclude that the minimum value of WACC is 5%, even though there are lower values of WACC than 5%, but at a lower frequency than that of values of 5%. The study’s results are anticipated to introduce additional findings to help other authors to understand the mechanism of optimizing the capital structure and reduce the risk in the gas and oil sector.

Keywords: capital structure; Monte Carlo simulation; weighted average cost of capital; Python; sensitivity; analysis; equity; debt; value of firm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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