A spline-DCS model is developed to forecast the conditional distribution of high-frequency financial data with periodic behavior. The dynamic cubic spline of Harvey and Koopman (1993) is applied to allow diurnal patterns to evolve stochastically over time. An empirical application illustrates the practicality and impressive predictive performance of the model.