Semiparametric Modeling of Stochastic and Deterministic Trends and Fractional Stationarity

The distinction between stationarity, difference stationarity, deterministictrends as well as between short- and long-range dependence has a major impact onstatistical conclusions, such as confidence intervals for population quantities or point and interval forecasts. SEMIFAR models introduced by [6] provide a unified approach that allows for simultaneous modelling of and distinction between deterministic trends, difference stationarity and stationarity with short- and long-range dependence. In this paper, recent results on the SEMIFAR models are summarized and their potential usefulness for economic time series analysis is illustrated by analyzing several commodities, exchange rates, the volatility of stock market indices and some simulated series. Predictions combine stochastic prediction of the random part with functional extrapolation of the deterministic part.