The prominence of stationarity in time series forecasting

Abstract

The stationarity of a time series can have a significant influence on its properties and forecasting behaviour, where the inability to render a time series to the correct form of stationarity can lead to spurious results. Although there are several different approaches to render a non-stationary time series stationary, few econometricians look past the first differencing method. This paper employs a novel process to determine whether using the correct form of stationary data will enhance forecasting accuracy. The results from this paper substantiate the hypothesis that the correct form of stationarity will outperform any other form of stationarity.