SEMIFAR forecasts, with applications to foreign exchange rates |
| |
Authors: | Jan Beran Dirk Ocker |
| |
Institution: | University of Konstanz, Department of Mathematics and Computer Science, Universitätsstr. 10, Postfach 5560, 78457 Konstanz, Germany |
| |
Abstract: | SEMIFAR models introduced in Beran (1997. Estimating trends, long-range dependence and nonstationarity, preprint) provide a semiparametric modelling framework that enables the data analyst to separate deterministic and stochastic trends as well as short- and long-memory components in an observed time series. A correct distinction between these components, and in particular, the decision which of the components may be present in the data have an important impact on forecasts. In this paper, forecasts and forecast intervals for SEMIFAR models are obtained. The forecasts are based on an extrapolation of the nonparametric trend function and optimal forecasts of the stochastic component. In the data analytical part of the paper, the proposed method is applied to foreign exchange rates from Europe and Asia. |
| |
Keywords: | Trend Differencing Long-range dependence Difference stationarity Fractional ARIMA Box–Jenkins ARIMA BIC Kernel estimation Bandwidth Semiparametric models Forecasting |
本文献已被 ScienceDirect 等数据库收录! |
|