ARIMA models have been extensively used for property market modelling.Property researchers have used this type of univariate forecasting technique to predict property rents, returns and yields.However, it has been indicated that ARIMA models could be improved.Accordingly, the current research examines an alternative specification of the ARIMA technique.The proposed model replaces the AutoRegressive (AR) element with Simple Exponential Smoothing (SES) element within the ARIMA framework.This creates a SESMA model.The empirical results indicate that this mathematical manipulation improves model out-of-sample forecasting accuracy.This therefore suggests that the SESMA model could successfully be employed for short-term investment decision-making.