to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the … focus on fit in-sample, but SVR considers both fit and forecast out-of-sample which endows SVR with an excellent forecasting …

employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing …. To evaluate ex-ante forecasting performance for particular rates, different forecast features such as mean squared errors … offers additional forecast accuracy in terms of directional accuracy and big hit ability. …

improve the forecast performance compared to the benchmark models estimated for each of the provinces separately. It was also … shown that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast … accuracy gain as measured by the root mean squared forecast error is about 8% at 1-year horizon and exceeds 25% at 13- and 14 …

alternative during the 2008m1-2009m5 forecast period. In addition, Google indicators are available at weekly frequency and not …

Swiss GDP. We find that the factor model offers a substantial improvement in forecast accuracy of GDP growth rates compared … to a benchmark naive constant-growth model at all forecast horizons and at all data vintages. The largest forecast …