This paper reconciles the relative pricing controversy between DeBondt and Thaler (1985, 1987), Chan (1988), and Ball and Kothari (1989). The negative autocorrelation in long-horizon index returns, along with the selection criterion of the contrarian strategy, can explain the positive covariance between time-varying betas and risk premiums. However, test-period beta estimates reflect the reversal of earnings expectations associated with underlying factors. The controversy thus reduces to the debate of Fama and French (1988) and Poterba and Summers (1988) over the source of the temporary price components in the market index. Rational changes in expected returns and cash flows explain most of the cross-sectional variation in returns.

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.

The authors examine the returns of stocks in the Cowles Industrial Index before and after the introduction of personal income taxes in 1917. This is distinct from earlier studies because they cross-sectionally analyze the relationship between the returns of the individual stocks and measures of tax-loss selling potential and size. The authors find that excess returns at the turn-of-the-year and for the month of January were not significant until after 1917. These results provide strong support for the tax-loss selling hypothesis as an explanation for the January seasonal in the returns of small firms.

ABSTRACT We examine the returns of stocks in Cowles Industrial Index before and after the introduction of personal income taxes in 1917. This is distinct from earlier studies because we cross‐sectionally analyze the relationship between the returns of the individual stocks and measures of tax‐loss selling potential and size. We find that excess returns at the turn‐of‐the‐year and for the month of January were not significant until after 1917. These results provide strong support for the tax‐loss selling hypothesis as an explanation for the January seasonal in the returns of small firms.