This paper provides analyses of daily retail data, extracting annual and weekly seasonal patterns along with moving holiday effects, using an unobserved components framework. It is shown that the weekly seasonality, which corresponds to the trading day effect observed in monthly time series, can be treated in a dynamic framework via stochastic unobserved component models. A secondary result is the measurement of economically signicant holiday effects in retail sector data, where the impact of Black Friday, Cyber Monday, Easter, Superbowl Sunday, and Labor Day is explicitly determined.