The paper develops the net proceeds maximization theory explaining how the spread and offering price are determined in all underwritten offerings in the U.S. The theory yields solutions for the optimal spread and offering price for all underwritten securities and it yields comparative statics that explain the cross-sectional variation in actual spreads and initial returns across different types of underwritten securities. The theory also suggests two alternative explanations to the ones offered by Chen and Ritter (J. Finance 55 (2000) 1105) for the clustering of unseasoned equity offerings spreads at 7%.

We model the risk of setting the required fixed-offer price in an IPO given initial uncertainty about value, as well as costs of over and underpricing. Assuming that the goal of issuers in bookbuilt IPOs is to maximize net offering proceeds, our analysis indicates that their optimal strategy is to negotiate a relatively small spread, consistent with material underpricing. Similarly, considering the expected costs of overpricing makes the underpricing of best-efforts IPOs in the interest of issuers. Our results rely on neither asymmetric information nor agency costs and provide support for Hansen's (2001) nearly-optimal “conventional” spread and the view that it evolved from adaptive, imitative behavior, consistent with Alchian's (1950) explanation of how economic players evolve practices to survive under uncertainty and incomplete information, as well as Alchian's (1969) work on how fixed prices and queues can efficiently clear product markets.

We show how bias can arise systematically in the beta estimates of extreme performers when long-run return reversals are present and partly, or wholly, due to sign changes in unanticipated factor realizations. Our evidence is consistent with this bias being responsible for the large shifts in the beta estimates of extreme performers, more so than the leverage effect, which has been the predominant explanation in prior literature. Bias in these contemporaneous realized betas, estimated with the same returns that are to be risk adjusted, arises due to the general problem of “overconditioning,” where betas are estimated conditional on information that is not yet known. Several methods for conditioning betas on out-of-sample returns are evaluated and found to be lacking, although some offer improvement under certain circumstances. We also show evidence of this bias in the Fama–French Three-factor loadings of extreme performers. Our findings indicate not only that previous studies of long-run reversals understate contrarian profits but that bias is prevalent in the OLS beta estimates of extreme performers, and this has implications for estimating the cost of capital and measuring long-run performance. We offer recommendations for identifying when this bias is likely present, as well as general methods to correct for it.