Standard daily financial time series analyses using autoregressive (AR) models typicallydisregard weekends following the trading time hypothesis (TTH) because the relevant assetsof the models are not traded (and thus, their prices are not observed) on weekends. However,weekends may affect asset prices through time discounting as well as through shocks/newsoccurring on weekends. In this regard, we suggest a test for the TTH by using an AR(1)model, where many asset prices are closely approximated by an AR(1) process. The proposingtest statistics are based upon the differences of AR coefficients and error variances betweenMonday and the other weekdays. Asymptotic normality of the suggested test statistics underthe TTH and model stationarity is proved. Under the model of nonstationarity, the teststatistic is asymptotically pivotal/non-standard and the critical values are given from theMonte Carlo simulations. In an application for the United States S&P 500 data during theyears 2000-2011, we found that the TTH was rejected, particularly during the years of warand financial crisis. We also confirmed a weakening of the weekend effect as depicted inChow, Hsiao and Solt (2003), and Connolly’s (1989) results. It requires us to revise thedynamic analyses using a time series model of asset prices considering the weekends.