Multiple-Merger and Acquisition (M&As) Study with Explanatory Series

Mergers and acquisitions have long been the most favored methods not only for growth but also organizational administrative/economic corrections. This technique is used in banks for strategic business reasons that are mostly economic in nature. The main motivation behind present study is to propose a multiple-merger autoregressive explanatory (MM-ARE) model. The primary objective of the present study is to examine the impact of merger and acquisition, by which one can understand the impact of merger in the parameters as well as model behavior. For this objective, we are assuming informative priors to calculate the conditional posterior density and generate the samples by using Gibbs sampling methods under symmetric and asymmetric loss functions. The methodologies proposed here are illustrated by means of simulation study and a real data analysis.