Эта работа вносит свой вклад в изучение темы слияний и поглощений (M секторе основное,). Слияния и поглощения - это класс экономических процессов консолидации бизнеса и капитала, происходящих на макро- и микроэкономическом уровнях, в результате которых на рынке появляются более крупные компании. Целью данной магистерской диссертации является изучение взаимосвязи между различными детерминантами...о... сделок и количеством слияний и поглощений. Данное исследование проводится на двух уровнях, первый из которых - страновой, где гдеяющ ER внимание сосредоточено на макроэкономических показателях и их влиянии на количество сделок слияния и поглощения. Второй уровень посвящен анализу транзакций в конкретной отрасли, а именно IT-секторе США секторе основное), где представлены крупнейшие компании отрасли в целом. Сбор данных проводился в цифровой среде с помощью инструментов синтаксического анализа, автоматизированных инструментов Python. Анализ и обработка данных осуществлялись с использованием программного обеспечения STATA, а именно.

This work contributes to the topic of Mergers and Acquisitions (M&As). Mergers and acquisitions are a class of economic processes of consolidation of business and capital, occurring at the macro- and microeconomic levels, as a result of which larger companies appear on the market. The purpose of this masters thesis is to examine the relationship between various determinants and the number of mergers and acquisitions. This study is conducted at two levels, where the first is the country level, where the focus of the study is based on macroeconomic indicators and their impact on the number of M&A transactions. The second level is devoted to the analysis of transactions in the concrete industry, namely the US IT sector, where the largest companies in the industry as a whole are represented. Data collection was carried out in a digital environment by parsing tools, automated Python tools. Data analysis and processing was carried out using STATA software, namely, regression analysis was carried out, according to the results of which the best model was selected from OLS models, models with fixed effects and with random effects. This technique was followed at both levels of the study. The number of mergers and acquisitions is set as a dependent variable. Based on the results of the model construction, it was possible to identify significant factors at each level, at the country level, these determinants were GDP per capital, unemployment rate (UR), government bonds yield, business freedom index, the number of patent applications, market capitalization of domestic companies and domestic credit to private sector. When analyzing the IT sector, the return on assets, the size of the company, total return, price-to-equity and current ratio turned out to be significant factors. This work contributes to the issue of the impact of the specifics of the country on the number of mergers and acquisitions around the world.