We develop an easy-to-implement method for forecasting a stationary auto-regressive fractionally integrated moving average (ARFIMA) process subject to structural breaks with unknown break dates. We show that an ARFIMA process subject to a mean shift and a change in the long memory parameter can...

This paper proposes a monitoring cumulative sum of squares (CUSQ)-type test for structural breaks in real-time via an auto-regressive (AR) approximation framework when data generating process (DGP) is a long memory process. The limiting distribution of the monitoring test follows a Brownian...