We analyze the use of alternative trading systems in a large sample of institutional orders and the trades that constitute these orders. Proprietary data allow us to distinguish between orders and trades filled by day and after-hours crossing systems, electronic communication networks (ECNs), and traditional brokers. Controlling for variation in order and security characteristics, as well as endogeneity in the choice of trading venue, we find that realized execution costs are generally lower on alternative trading systems. Order handling rules and tick size changes implemented in 1997 appear to have reduced the cost advantage of trading on ECNs.

We assess the profitability of momentum strategies using a stochastic discount factor approach. In unconditional tests, approximately half of the strategies' profitability is explained. In conditional tests we see a further slight decline in profits. We argue that the risk of these strategies should be increasing in the market risk premium. Empirically, while their risk measures estimated relative to the stochastic discount factor behave as predicted, market betas do not; thus capital asset pricing model (CAPM)-like benchmarks may lead to incorrect inferences. Given that our nonparametric risk adjustment explains roughly half of momentum strategy profits, we cannot rule out the possibility of residual mispricing.

We assess the profitability of momentum strategies using a stochastic discount factor approach. In unconditional tests, approximately half of the strategies' profitability is explained. In conditional tests we see a further slight decline in profits. We argue that the risk of these strategies should be increasing in the market risk premium. Empirically, while their risk measures estimated relative to the stochastic discount factor behave as predicted, market betas do not; thus capital asset pricing model (CAPM)-like benchmarks may lead to incorrect inferences. Given that our nonparametric risk adjustment explains roughly half of momentum strategy profits, we cannot rule out the possibility of residual mispricing.

Abstract The fragility of the CAPM has led to a resurgence of research that frequently uses trading strategies based on sorting procedures to uncover relations between firm characteristics (such as “value” or “glamour”) and equity returns. We examine the propensity of these strategies to generate statistically and economically significant profits due to our familiarity with the data. Under plausible assumptions, data snooping can account for up to 50 percent of the in‐sample relations between firm characteristics and returns uncovered using single (one‐way) sorts. The biases can be much larger if we simultaneously condition returns on two (or more) characteristics.