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

摘要

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 M6;A characteristics such as corporate free cash flow, holding proportion of large shareholders, State-owned share ratio, M6;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 M6;A transaction. For the second year following M6;A transaction, corporate free cash flow per share significantly negatively impacts the performance. However, there are no significant evidence that the M6;A characteristics affect the performance of merger for the third year after M6;A transaction and the year of M6;A. The explanational powers of our regression models for the first two years following M6;A transaction are obviously higher than that of previous research, which suggests that our regression models adequately reflect the nonlinear relationship between M6;A characteristics and post-merger performance.