Previsão do perfil das instituições envolvidas em estratégias de Fusões e Aquisições (F&A) do setor bancário brasileiro

Abstract

The objective of this work was to identify the importance of economic and financial variables for the occurrence of mergers and acquisitions (M&A) in the Brazilian banking sector after 20 years of consolidation of the real plan, a period between the years 1995 and 2015. Discriminant analysis, logistic regression, neural networks and a hybrid model were used. In general, it was observed that the indicators of asset quality, profitability, liquidity, efficiency and size of the firm were important in discriminating the groups of banks studied (acquirers and acquired) and it was possible to verify that banks with higher indicators are more likely to become purchasers. Regarding the methods used, it can be said that the models showed adherence to the data studied, however, the superiority of artificial neural networks in their traditional and hybrid form is emphasized. Finally, the importance of work like this in emerging markets is emphasized, and forecasting models can bring more security and mitigate the risks assumed by investors. Furthermore, they provide useful information for business decision making, since they list important variables for the classification of target and non-target M&A companies.