A Methodological Study on Selection of Comparable Companies for Mergers and Acquisitions of Listed Companies Based on KNN Algorithm

With the frequent occurrence of mergers and acquisitions (M&As) by listed companies, valuation has become an important component of the M&A process. This study first analyzes the current situation of comparable companies in the valuation of mergers and acquisitions of listed companies, and divides the impact of comparable company selection into industry level and enterprise level. This study analyzed the distribution characteristics of comparable companies through Gini coefficient analysis. Simultaneously use the K-Nearest neighbor algorithm for high-dimensional similarity matching to screen comparable companies. The results show that when $K=5$ is set, 5 most similar companies can be obtained as comparable companies. The average price to book ratio of the 5 comparable companies is 2.51, and the difference rate from the average price to book ratio of comparable companies is 20.15%, which is within an acceptable range. Therefore, the rationality of the model for selecting comparable companies can be verified.