Stock flippers pose a problem for underwriters of initial public offerings (IPOs). They subscribe to the issue, but immediately resell their shares, which may depress the aftermarket price. This paper presents a model of how stock flippers affect IPO pricing. The model shows that the underwriter chooses whether to price the issue as a cold, weak, or hot IPO. Stock flippers have the greatest effect on pricing in weak IPOs and provide an explanation for underwriter stabilization. In contrast to existing models of stabilization, the underwriter gains from after-market purchases, particularly if the contract with the issuer includes an over-allotment option. The over-allotment option encourages a lower offer price, which may lead to under-pricing. These results correspond to recent findings on IPO returns and underwriter stabilization activities.

We analyze allocations to institutional and retail investors in 441 initial public offerings (IPOs). In addition to the well-known favorable first-day returns, we show that institutions also obtain more allocations in IPOs with better long-term performance. We find that initial institutional flips help predict future returns, suggesting that at least some institutions retain valuable private information about IPO firms. Collectively, these findings illustrate the importance of aftermarket relations between underwriters and investors and that underwriters have discretionary means to compensate IPO investors beyond first-day returns and price stabilization.

We examine whether speed is an important characteristic of traders who anticipate local price trends. These anticipatory participants correctly trade prior to the overall market and systematically act before other participants. They use manual and algorithmic order entry methods, but most are not fast enough to be high frequency traders (HFTs). Those anticipating price trends have impacts as if they are informed traders, while the case for anticipatory participants affecting the volume of other traders is rejected. A follow-up sample shows significant attrition in accounts and difficulty maintaining the anticipatory strategies. To identify anticipatory traders, we devise novel methods to isolate local price trends using order book data from the West Texas Intermediate (WTI) crude oil futures market.