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Fuzzy Logic And The Cognition And Reaction Of Investors After The Merger Announcement

Posted on:2019-08-04Degree:MasterType:Thesis
Country:ChinaCandidate:H F WuFull Text:PDF
GTID:2429330542972089Subject:Business Administration
Abstract/Summary:PDF Full Text Request
In recent years,with the continuous development of China's capital market,mergers and acquisitions of listed companies has become an important part of enterprise strategic transformation and market resource allocation.Theory and practice realm are eager to make clear about how investors make decisions after a M&A announcement,but relevant research remains controversial,the study of the influence of individual factors which relies on regression analysis is increasingly questioned especially,and academics begin to study how multivariate combinations(configurations)affect investor awareness of M&A.Based on the comparative analysis of 56 M&A events of listed companies in China,this paper discusses the combination of influencing factors of investors' cognition and response after M&A announcement,and compares them with Campbell et al.(2016).The result shows that after the merger announcement,the cognitive process of Chinese investors also has the characteristics of the whole configuration.There are five factors combinations that lead to positive(negative)reaction to in the stock market.Compared to North America,China's M&A situation is more complex and diverse.Investors in the two major capital markets recognize the different levels of sensitivity to different trading motives.There is a typical transaction of "expert diversification strategic investment" in the Chinese market;Chinese investors will focus on the negative effects of the lack of experience in identifying"negative" transactions.The results of this paper provide a useful reference for the market response of listed companies to effectively manage M&A announcements.
Keywords/Search Tags:Mergers and acquisitions of listed companies, Investors, Qualitative comparative analysis, The market reaction
PDF Full Text Request
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