Prior research addressing questions such as whether investors respond to a hypothesized information event used tests of unusual return and/or trading activity as alternative measures of investor response. We investigate which of these two metrics maximizes the likelihood that a researcher correctly detects the presence or absence of a response. Building on the repeated-sample framework established in Brown and Warner (1980, 1985) and Dyckman et al. (1984), we provide evidence that (1) volume-based metrics, especially measures based on numbers of transactions, provide more powerful tests of investor response to public disclosures than do return-based metrics; and (2) supplementing return-based measures with trading-based measures increases the power of tests designed to detect investor response. Our conclusions are particularly relevant when power is critical (i.e., when sample sizes are small or anticipated investor response is small). Our evidence also suggests that before concluding that investors do not respond to a public disclosure, based on a returns analysis, researchers should confirm the nonresponse inference with trading-based measures.