This study examines some diagnostics available in X-13ARIMA-SEATS for detecting a trading-day effect. The diagnostics of interest are a χ²-test, an F-test, and the spectrum peaks at the two tested trading-day frequencies (under both the default last 8 years of data as used by the program and the full data). Sets of seasonal series without trading-day effects are simulated initially to measure the false detection rate and to estimate the appropriate α = 0 .05 critical value. Sets of seasonal series with trading-day effects are subsequently simulated to assess the power of those diagnostics.