Mutual funds experiencing large outflows (inflows) tend to decrease (expand) their positions, creating downward (upward) price pressure in the stocks held in common by them (Coval and Stafford [2007]). This study shows that corporate insiders exploit the resulting mispricing by buying (selling) their company's stock if it is subject to such fire sales (purchases) by funds. We also show that the likelihood of option grants is greater for stocks that are subject to mutual fund fire sales. Finally, we show that both the insider trading and the option granting activities help speed up the correction of the flow-driven mispricing. Overall, this study illustrates that insiders enhance personal benefits by trading on their personal account and influencing the timing of option grants in response to mispricing due to flow-driven fund trading. Moreover, these activities help improve the informational efficiency of stock price.

Between 1995 and 2006 about a quarter of merging firms hired boutique banks as their advisors on mergers and acquisitions (M&A). Boutique advisors, often specialized by industry, are generally smaller and more independent than full-service banks. This paper investigates firms' choice between boutique and full-service advisors and the impact of advisor choice on deal outcomes. We find that both acquirers and targets are more likely to choose boutique advisors in complex deals, suggesting that boutique advisors are chosen for their skill and expertise. After controlling for the endogenous choice of advisors, we find lower deal premiums when acquirers hire boutique advisors. In addition, boutique advisors spend more time, probably on due diligence and negotiation, to complete deals. Overall, our findings suggest that boutique advisors are chosen in more complex deals and they achieve more favorable deal outcomes.

Major customers in strong bargaining position can exert pressure on dependent suppliers and adversely affect their financing conditions. Consistent with this prediction, our analysis shows that the concentration of customer bases can enhance the bargaining power of downstream customers in supplier-customer interactions, leading to the significant deterioration of financing constraints for upstream firms. We then introduce a novel machine-learning approach to analyze the heterogeneous effect of customer concentration. This allows us to identify approximately 15 % of the firms, especially those small non-SOEs, as most vulnerable to customer concentration as the bargaining effect dominates.