The paper studies both the initial and aftermarket performance (measured by risk-adjusted returns) on newly issued common stocks which were offered to the public during the 1960s. The results confirm that average initial performance is positive (11.4 percent), while the distribution of returns is skewed so that the subscriber of a single random new issue offering has about an equal chance for gain or loss. The results are generally consistent with aftermarket efficiency. Positive initial performance along with aftermarket efficiency indicate that new issue offerings are underpriced. The paper provides insights into this underpricing mystery, but does not solve it.

Hot markets, which refer to instances when stocks increase their offering prices to a level greater than average market premiums, have been overlooked in recent academic literature. Thus, this research examines factors which may aid in the prediction of hot issue markets. A sample of unseasoned stock issues offered between January 1, 1960 and October 31, 1970 is compiled, noting the stock's original offering price and their first two months' ending bids. In order to understand overall market performance during this time, data was also collected from the daily Standard & Poor 500 (SP the correlation between new issue premiums and aftermarket performance; the association between the number of monthly new offerings and simultaneous new issue premiums; and finally the correlation between new issue premiums and past market performance. Several implications for investors, issuers, and researchers are presented, as are directions for future research. The findings indicate that a level of predictability exists within the first month's residuals, which has implications for the timing of offerings and new issue purchases. A higher offering price, when compared to a cold issue market's efficient prices, may be obtained by issuers during that first month's issuance. (AKP)

[Recent evidence suggests that past mutual fund performance predicts future performance. We analyze the relationship between volatility and returns in a sample that is truncated by survivorship and show that this relationship gives rise to the appearance of predictability. We present some numerical examples to show that this effect can be strong enough to account for the strength of the evidence favoring return predictability.]

Recent evidence suggests that past mutual fund performance predicts future performance. We analyze the relationship between volatility and returns in a sample that is truncated by survivorship and show that this relationship gives rise to the appearance of predictability. We present some numerical examples to show that this effect can be strong enough to account for the strength of evidence favoring return predictability. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

Hendricks, Patel, and Zeckhauser (1997) (HPZ) find that the response of current to past returns for mutual funds in the presence of survivorship is nonlinear. In our rejoinder to their paper, we verify their results through simulation, provide some intuition for why the result is true, and evaluate the power of their proposed test based upon the J - shape pattern. Theirs is a useful contribution to the growing literature about the issue of survival biases in empirical finance. It may help to explain puzzling results reported in the mutual fund literature, and may provide a guide for future experimental design. Our investigation of the HPZ results led us to a more complete understanding of how differential volatility affects survival - conditioned returns. Our simulations of the test statistic proposed by HPZ suggest that the power of the test is dependent on the absolute level of the threshold, as well as on the magnitude of the cross - sectional differences in variance. While it would be useful to have a reliable test of the conjecture that survivorship is not driving an observed empirical result, we are only beginning to understand the kind of empirical regularities that survival may induce.