A general approach to testing serial dependence restrictions implied from financial models is developed. In particular, we discuss joint serial dependence restrictions imposed by random walk, market microstructure, and rational expectations models recently examined in the literature. This approach incorporates more information from the data by explicitly modeling dependencies induced by the use of overlapping observations. Because the estimation problem is sufficiently simple in this framework, the test statistics have simple representations in terms of only a few unknown parameters. As a result, relatively good size properties are attained in small samples. In addition, the benefit to overlapping observations and the advantage of examining multiperiod time series are explicitly quantified.