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Title: Reputation-quality mechanism in the context of mergers and acquisitions : financial advisors, financial analysts and acquirer performance
Author: Xing, Xiaofei
ISNI:       0000 0004 5921 5612
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2016
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This thesis focuses on the reputation–quality mechanism in the context of mergers and acquisitions (M&A). This study specifically examines whether investment bank reputation is a determinant of M&A advisory service quality, and whether sell-side analyst reputation is a determinant of the predictive ability of stock recommendations. To begin with, this research investigates whether top-tier M&A financial advisors improve their acquirer clients’ performance in both the short and long term, and whether top-tier advisors can help their acquirer clients to gain bargaining advantage, allowing them to pay lower bid premiums. I find that acquirers advised by top-tier advisors outperform in the long term and pay lower bid premiums, suggesting that top-tier advisors do have superior skills. Furthermore, the social loafing hypothesis suggests that individuals exercise less effort when they work collectively. My research therefore explores whether multiple top-tier financial advisors can cooperate effectively to create value for their clients or whether they suffer from social loafing. This study finds that acquirers advised by multiple top-tier advisors gain greater long-term returns and pay lower bid premiums than acquirers advised by a single top-tier advisor. The results suggest that top-tier advisors care more about their reputational capital, and therefore do not suffer from social loafing. Instead, they can make concerted efforts to improve their clients’ performance and bargaining power. In addition, my study examines whether the pre-acquisition stock recommendations of sell-side analysts can be used to predict acquirer performance, and more importantly whether the recommendations of star analysts have stronger predictive ability for acquirer announcement performance than those of non-star analysts. I find that pre-deal consensus recommendations are an effective predictor of acquirer performance; however, star recommendations are not predictive of acquirer performance, while acquirers with more favourable non star consensus recommendations gain higher announcement returns. In other words, non-star recommendations have stronger predictive ability than star recommendations. Overall, this thesis provides new evidence on the reputation–quality mechanism in the context of M&A. The results suggest that market share-based league tables are reliable to reflect financial advisors’ skills, while sell-side analyst rankings are a kind of popularity contest.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available