Empirical Analysis On Stock Price Effects Of M&A Of Listed Companies

M&A led to the variation of stock price of the target company, so it changed the value of the target company. This paper carries on an empirical analysis from the departure point of the effect of M&A on the performance of the listed target firm. Following the traditional research pattern, this article first reviews the extant empirical researches in this field then clarifies the concepts of M&A and its effect and points out the possible mechanism behind the effect of M&A on the performance. Next, the author comes up with the research method of this article, based on detailed review on the extant empirical research methodology in this field. Last, this paper uses event study framework which is adjusted by a bivariate GARCH model to test 51 events of M&A of listed companies in China in 2003. All of the sample events are cases that corporate control is switched by equity transferring.The result indicates that M&A brings significant value increase to the target company but the value-increasing effect is insignificant within a longer event window . The different acquisition strategies of the bid company result in different effect on the target firm: The types of specialization of operation and diversification of geography of M&A have the rather big probability to increase the value of the target company. While the M&A which aims in diversifying the business and the location can not increase the value of the acquired firm significantly.Our research method is different from that of the extant study in three aspects. Firstly, the existing empirical researches categorize M&A from the angle of industry, acquisition approach and equity structure while this paper does this from perspective of diversification and specialization. Secondly, domestic researches on this field usually mix the acquiring firm and acquired firm or only analyze the bidding company while this article attach importance to discuss the effect of M&A on the value of the target firm. Last, this paper utilizes a Bivariate GARCH model to compute the cumulative abnormal return (CAR), which avoids wrong CAR resulted from mistaken the characteristic ofβ.