Numerous studies have examined the mean/variance efficiency of various market proxies by employing sample parameters and have concluded that these proxies are inefficient. These findings cast doubt about the capital asset pricing model (CAPM), one of the cornerstones of modern finance. This study adopts a reverse-engineering approach: given a particular market proxy, we find the minimal variations in sample parameters required to ensure that the proxy is mean/variance efficient. Surprisingly, slight variations in parameters, well within estimation error bounds, suffice to make the proxy efficient. Thus, many conventional market proxies could be perfectly consistent with the CAPM and useful for estimating expected returns.

Bid–ask spreads in equities have declined on average but have become increasingly right-skewed. This finding holds across exchanges as well as size, price, and volume quartiles. Higher right-skewness is consistent with more competition among market makers; which may reduce cross-subsidization across periods of high and low asymmetric information, unlike a monopolistic regime that can maintain a relatively constant spread. Confirming this intuition, proportional differences in spreads between earnings announcements and normal periods have increased considerably even as trading costs have declined on average. Skewness also is cross-sectionally related to information proxies such as institutional holdings and analyst following.

Many takeovers occur after one-on-one negotiations, which suggests a troubling lack of competition. We seek to determine whether acquirers in such friendly deals are truly insulated from competitive pressures. We study two countervailing influences: (1) potential but unobserved latent competition, i.e., the likelihood that rival bidders could appear, and (2) anticipated auction costs when negotiations fail. Using various proxies, we find that latent competition increases the bid premium offered in negotiated deals and that auction costs reduce the premium.

Relatively little is known about the trading volume in derivatives relative to the volume in underlying stocks. We study the time-series properties and the determinants of the options/stock trading volume ratio (O/S) using a comprehensive cross-section and time-series of data on equities and their listed options. O/S is related to many intuitive determinants such as delta and trading costs, and it also varies with institutional holdings, analyst following, and analyst forecast dispersion. O/S is higher around earnings announcements, suggesting increased trading in the options market. Further, post-announcement absolute returns are positively related to pre-announcement O/S, which suggests that at least part of the pre-announcement options trading is informed.