Post-Merger Financial Performance – A Study of High-Tech Companies in the United States using Artificial Neural Networks

Abstract

The debate about the efficacy of mergers and acquisitions as a growth strategy in terms of ex-post value creation has been developing for decades. This paper aims to create an artificial neural network that examines trends in the financials and marks the potential sources of value creation in the high-tech industry mergers between 2011 and 2021. The findings demonstrate that ANN can be implemented as a highly efficient model for analyzing complex financial events due to its flexibility and lack of prior assumptions about the data.