Predicting M&A Deals with Financial Results of the Companies

Mergers and acquisitions (M&A) are part of the lifecycle for the majority of companies. It is an important stage of future growth and development of companies. In addition, it is an opportunity for financial advisors and investors to rebalance their portfolio and earn abnormal return on information about future transactions. Almost all papers about prediction of M&A were focused on predicting targets and determination factors which increase probability of the company to be target. However, the main aim of this work is to introduce a model which helps to calculate the probability that the company will be an acquirer in the next 12 months. This work was based on a sample of 1500 USA public companies and a probit model was used. The variables of the model were relative change in the different financial accounts of the company in the past two and three years before M&A deal. During estimation of the model, we find financial results which have the highest effect on the probability of the company to be an acquirer. We receive significant results that companies with growth in Price to earnings ratio and in cash level have higher probability to be acquirer. The next result is about leverage. Companies with growth in leverage and as a result decrease in debt capacity have lower probability to be acquirer. In addition, we get significant results that companies from sector associated with technology development have higher probability to be acquirer. Key words: acquirer prediction, relative change in financial results.