Análise da volatilidade dos retornos nos processos de fusões e aquisições brasileiros: um estudo com dados de alta frequência

• Ano de defesa: 2018
• Autor(a) principal: Barbara Cristina Sacramento Coelho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Modelos ARCH; Volatilidade Anormal Média; Volatilidade dos Retornos; Fusões e Aquisições; Dados Intradiários; Administração de empresas; Empresas Fusão e incorporação; Investimentos
• Link de acesso: http://hdl.handle.net/1843/BUOS-BA8FVP

M&A processes have been increasingly used by companies as an important growth strategy in the face of a new agenda in the world economic scenario in which there is a growing integration and interdependence between markets, increased uncertainty and consequently , intensification of competition. Although these operations apparently provide economic benefits, such as gains in scale and market power, they are permeated by a high degree of complexity, risk and uncertainty, which can be quantified through a proxy, volatility. Its measurement is fundamental for the establishment of investment strategies in the financial markets, and therefore, in this dissertation, the objective is to analyze whether, in view of the announcement of the occurrence of an M&A process, the volatility of the Brazilian stock returns is affected . For such analysis, intraday (high frequency) data were used, at 15 minute intervals, including the stock market pre-opening period and the after market. In order to estimate volatility, we used the conditional heteroscedastic model that best fit the estimation of returns volatility - Generalized Autoregressive Conditional Heteroscedasticity (GARCH) or Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). We analyzed 35 M&A events of Brazilian companies listed in B3 that occurred between 2009 and 2017. In a similar way to an event study, however, using conditional heteroscedastic models, we tried to evaluate, through the Wilcoxon test (non-parametric), if the average abnormal volatility before the F & A announcement is statistically equal to the average abnormal volatility after the announcement. We compared the means of five windows with intraday data before and after the event, corresponding to the days -30 to -11, -10 to -1, -2 to -1, 0 to +2 and 0 to +1, 0, being 0 the day of the M&A announcement. For 32 of the 35 events, there was a difference between the average abnormal volatility before and after the announcement, possibly showing that the M&A processes affect the volatility of returns, although no positive or negative definite trend was observed. In practical terms, the results obtained help companies and investors to perceive the impact of M&A's announcement on the volatility of returns by changing the risk level of these processes in order to promote adjustments in expectations and guide investment decision making. In theoretical terms, this work contributes to partially fill the existing void of volatility in M&As processes.