Use of statistical methods and methods of imitation modeling in the analysis of consolidation processes risks
Автор: Izhevsky V.L., Atapina N.V., Kononov V.N.
Рубрика: Экономика и финансы
Статья в выпуске: 3 т.11, 2017 года.
Бесплатный доступ
Consolidation processes, which are processes of the companies' growth implemented by including other functioning economic entities into their structure, have become an integral part of the development of large corporate structures. At the same time, the long terms and cost of consolidation carry high risks of inefficiency of the consolidation process results, which is confirmed by the empirical studies. Therefore, an extremely relevant task is to quantify the risks for making a decision on the expedience of the consolidation process. The analysis of modern methodological apparatus for risk assessment shows that the most objective and accurate results can be achieved by using statistical methods and methods of simulation. To test the methods, the key risk factors that influenced the consolidation result were identified. They were classified into two groups: market risks, related to the change in the sensitivity of the group of business units to the external environment before and after consolidation, and investment risks, associated with the reassessment of a possible synergistic effect and underestimation of the emerging costs of consolidation and payment of a control premium. On the basis of data on a large industrial corporation, a financial model of consolidation results was constructed, based on net discounted cash flows before and after consolidation. The results obtained during the approbation can serve as an indirect explanation of the high proportion of inefficient consolidation processes: statistical probable deviations of the indicators as a result of the onset of risk situations completely overlap the possible benefits of consolidation.
Consolidation, consolidation processes, risks, risk-management, imitation modeling, monte-carlo method
Короткий адрес: https://sciup.org/147156379
IDR: 147156379 | DOI: 10.14529/em170307