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Моделирование цены сделок слияний и поглощений энергетических компаний: проблема выбора переменных

Authors: Prosvirina, I.I.; Sterkhov, A.V.; Batina, I.N.;

Моделирование цены сделок слияний и поглощений энергетических компаний: проблема выбора переменных

Abstract

Просвирина Ирина Игоревна, доктор экономических наук, профессор, Южно-Уральский государственный университет, Челябинск, Россия, email: iprosvirina@mail.ru Стерхов Александр Викторович, старший преподаватель, Уральский федеральный университет им. Первого Президента России Б.Н. Ельцина, Екатеринбург, Россия Батина Ирина Николаевна, кандидат экономических наук, доцент, Уральский федеральный университет им. Первого Президента России Б.Н. Ельцина, Екатеринбург, Россия Irina I. Prosvirina, Doctor of Sciences (Economics), Professor, South Ural State University, Chelyabinsk, Russia, email: iprosvirina@mail.ru Alexander V. Sterkhov, senior lecturer, Ural Federal University named after the First President of Russia B.N. Yeltsin, Yekaterinburg, Russia Irina N. Batina, Candidate of Sciences (Economics), Associate Professor, Ural Federal University named after the First President of Russia B.N. Yeltsin, Yekaterinburg, Russia Предметом исследования, результаты которого представлены в настоящей статье, выступает процесс формирования цены покупки-продажи в сделках слияний и поглощений. В связи с огромным количеством факторов, влияющих на результат подобных сделок, проблема выбора переменных для моделирования представляет собой сложную задачу. С целью решения этой задачи выделены два этапа исследования: выбор результирующей переменной и определение совокупности влияющих на данную переменную факторов. В результате большого количества итераций к числу основных групп переменных, значимость которых была установлена, отнесены показатели компании-объекта сделки, показатели компании-инициатора сделки, длительность этапов совершения сделки, параметры внешней среды, представленные величиной процентной ставки и индексом политической нестабильности, а также типы стратегий развития, используемые при планировании сделки. Особое внимание уделено выбору наиболее значимого по скорректированному коэффициенту детерминации показателя регрессии, отражающего размер активов компании. The subject of the study presented in this article is the process of formation of the price in mer-gers and acquisitions. Due to the huge number of factors that influence the result of such transactions, the problem of choosing variables for modeling is a difficult task. In order to solve this problem, two stages of the study are distinguished: the choice of the resulting variable and determining the combination of factors influencing it. As a result of a large number of iterations, the main groups of variables, the significance of which was established, has included the indicators of the target company, the indicators of the acquirer company, the duration of the stages of the deal, the parameters of the external environment represented by the interest rate and the index of political risks and vulnerabilities, as well as the types of corporate strategies used by the companies to plan transactions. Particular attention has been paid to the choice of the most significant regression indicator in terms of the adjusted coefficient of determination, reflecting the size of the company's assets.

Keywords

переговорный процесс, acquisitions, поглощения, mergers and acquisitions deal price, negotiation process, корпоративные финансы, слияния, modeling of mergers and acquisitions, электроэнергетика, electric power industry, эконометрическое моделирование, корпоративная стратегия, УДК 336.64, моделирование сделок слияний и поглощений, factors influencing the deal price, corporate finance, цена сделки слияния и поглощения, mergers, econometric modeling, факторы влияния на цену сделки, corporate strategy

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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Green