A study on the factors influencing post-merger performance of China's listed firms based on data mining

Abstract

Based on a sample of Mergers and Acquisitions of China's A-share listed companies during 2003–2005, this paper adopts multivariate adaptive regression splines model which is a newly developed data mining technique to analyze the nonlinear relationship between post-merger operating performance and M&A characteristics such as corporate free cash flow, holding proportion of large shareholders, State-owned share ratio, M&A premium, relative target size and industry relatedness of target and merger. The result demonstrates that corporate free cash flow per share has a nonlinear threshold effect on the first-year performance of merger subsequent to the M&A transaction. For the second year following M&A transaction, corporate free cash flow per share significantly negatively impacts the performance. However, there are no significant evidence that the M&A characteristics affect the performance of merger for the third year after M&A transaction and the year of M&A. The explanational powers of our regression models for the first two years following M&A transaction are obviously higher than that of previous research, which suggests that our regression models adequately reflect the nonlinear relationship between M&A characteristics and post-merger performance.